@article{ellegaard_bibliometric_2015, title = {The bibliometric analysis of scholarly production: {How} great is the impact?}, volume = {105}, issn = {0138-9130, 1588-2861}, shorttitle = {The bibliometric analysis of scholarly production}, url = {http://link.springer.com/10.1007/s11192-015-1645-z}, doi = {10.1007/s11192-015-1645-z}, abstract = {Bibliometric methods or ‘‘analysis’’ are now firmly established as scientific specialties and are an integral part of research evaluation methodology especially within the scientific and applied fields. The methods are used increasingly when studying various aspects of science and also in the way institutions and universities are ranked worldwide. A sufficient number of studies have been completed, and with the resulting literature, it is now possible to analyse the bibliometric method by using its own methodology. The bibliometric literature in this study, which was extracted from Web of Science, is divided into two parts using a method comparable to the method of Jonkers et al. (Characteristics of bibliometrics articles in library and information sciences (LIS) and other journals, pp. 449–551, 2012: The publications either lie within the Information and Library Science (ILS) category or within the non-ILS category which includes more applied, ‘‘subject’’ based studies. The impact in the different groupings is judged by means of citation analysis using normalized data and an almost linear increase can be observed from 1994 onwards in the non-ILS category. The implication for the dissemination and use of the bibliometric methods in the different contexts is discussed. A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact. A noticeable shift is observed in those countries which contribute to the pool of bibliometric analysis, as well as a self-perpetuating effect in giving and taking references.}, language = {en}, number = {3}, urldate = {2024-06-17}, journal = {Scientometrics}, author = {Ellegaard, Ole and Wallin, Johan A.}, month = dec, year = {2015}, pages = {1809--1831}, file = {Ellegaard et Wallin - 2015 - The bibliometric analysis of scholarly production.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\R5EZUKYG\\Ellegaard et Wallin - 2015 - The bibliometric analysis of scholarly production.pdf:application/pdf}, } @article{cvetkoska_enchanting_2023, title = {Enchanting performance measurement and management with data envelopment analysis: {Insights} from bibliometric data visualization and analysis}, volume = {9}, issn = {27726622}, shorttitle = {Enchanting performance measurement and management with data envelopment analysis}, url = {https://linkinghub.elsevier.com/retrieve/pii/S2772662223002072}, doi = {10.1016/j.dajour.2023.100367}, abstract = {While the breadth of applicative uses of data envelopment analysis (DEA) has increased over time, this non-parametric frontier methodology has proven effective for measuring how efficient decision-making units (DMUs) are. One of its uses is performance measurement in various organizations — from universities and banks to investment funds and entrepreneurial small and medium-sized enterprises. Following a search inquiry in the Scopus and Web of Science databases, we found no bibliometric analysis and keyword co-occurrence network visualization of just the use of DEA for performance management. With this study, we attempt to investigate the DEA literature for performance measurement and management, considering articles in scientific peer-reviewed journals, which are indexed in the Web of Science database. The analysis and visualization of the bibliometric data are based on 89 articles from the start of the century onward. We present the annual trends of published articles, journals, authors, and countries leading the scientific discussion and citation analysis. A detailed keyword visualization analysis was performed and is discussed in this article alongside the paths for future hotspots of the use of DEA for performance management. The findings have implications for both the academic community and practitioners, business leaders, managers, and policy-makers.}, language = {en}, urldate = {2024-06-17}, journal = {Decision Analytics Journal}, author = {Cvetkoska, Violeta and Eftimov, Ljupcho and Kitanovikj, Bojan}, month = dec, year = {2023}, pages = {100367}, file = {Cvetkoska et al. - 2023 - Enchanting performance measurement and management .pdf:C\:\\Users\\guillemi\\Zotero\\storage\\Y37I6874\\Cvetkoska et al. - 2023 - Enchanting performance measurement and management .pdf:application/pdf}, } @article{donthu_how_2021, title = {How to conduct a bibliometric analysis: {An} overview and guidelines}, volume = {133}, issn = {01482963}, shorttitle = {How to conduct a bibliometric analysis}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0148296321003155}, doi = {10.1016/j.jbusres.2021.04.070}, abstract = {Bibliometric analysis is a popular and rigorous method for exploring and analyzing large volumes of scientific data. It enables us to unpack the evolutionary nuances of a specific field, while shedding light on the emerging areas in that field. Yet, its application in business research is relatively new, and in many instances, underde­ veloped. Accordingly, we endeavor to present an overview of the bibliometric methodology, with a particular focus on its different techniques, while offering step-by-step guidelines that can be relied upon to rigorously perform bibliometric analysis with confidence. To this end, we also shed light on when and how bibliometric analysis should be used vis-`a-vis other similar techniques such as meta-analysis and systematic literature reviews. As a whole, this paper should be a useful resource for gaining insights on the available techniques and procedures for carrying out studies using bibliometric analysis.}, language = {en}, urldate = {2024-06-21}, journal = {Journal of Business Research}, author = {Donthu, Naveen and Kumar, Satish and Mukherjee, Debmalya and Pandey, Nitesh and Lim, Weng Marc}, month = sep, year = {2021}, pages = {285--296}, file = {Donthu et al. - 2021 - How to conduct a bibliometric analysis An overvie.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\PPFKTB3L\\Donthu et al. - 2021 - How to conduct a bibliometric analysis An overvie.pdf:application/pdf}, } @article{torres-salinas_foundations_2024, title = {Foundations of {Narrative} {Bibliometrics}}, volume = {18}, issn = {17511577}, url = {https://linkinghub.elsevier.com/retrieve/pii/S1751157724000592}, doi = {10.1016/j.joi.2024.101546}, abstract = {The document ’Foundations of Narrative Bibliometrics’ provides an analysis of the evolution of scientific assessment, highlighting the influence of manifestos such as DORA and CoARA in shaping ethical and responsible practices in academia, as well as their assimilation by Spanish scientific policies. It connects this context with the contributions of evaluative bibliometrics, emphasising the transition towards a more integrative approach that advocates for a balance between quantitative and qualitative methods in research evaluation. Furthermore, it underscores how the Narrative Curriculum has emerged as one of the fundamental tools in new evaluation processes, as it allows for the description of the complexity and context of academic achieve­ ments. Narrative Bibliometrics is proposed, defined as the use of bibliometric indicators to generate stories that support the defence and exposition of a scientific curriculum and/or its individual contributions within the framework of a scientific evaluation process, which demands narratives. To introduce the reader, it presents, in a non-exhaustive manner, sources, indicators, and practical cases for effectively applying Narrative Bibliometrics in various scientific evaluation contexts. Hence, this document contributes to the responsible use of bibliometric indicators, serving as a tool for evaluators and researchers.}, language = {en}, number = {3}, urldate = {2024-06-21}, journal = {Journal of Informetrics}, author = {Torres-Salinas, Daniel and Orduña-Malea, Enrique and Delgado-Vázquez, Ángel and Gorraiz, Juan and Arroyo-Machado, Wenceslao}, month = aug, year = {2024}, pages = {101546}, file = {Torres-Salinas et al. - 2024 - Foundations of Narrative Bibliometrics.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\H7WWWWG9\\Torres-Salinas et al. - 2024 - Foundations of Narrative Bibliometrics.pdf:application/pdf}, } @article{liu_scientometrics_2023, title = {Scientometrics of {Scientometrics} {Based} on {Web} of {Science} {Core} {Collection} {Data} between 1992 and 2020}, volume = {14}, copyright = {https://creativecommons.org/licenses/by/4.0/}, issn = {2078-2489}, url = {https://www.mdpi.com/2078-2489/14/12/637}, doi = {10.3390/info14120637}, abstract = {Scientometrics is a quantitative and statistical approach that analyzes research on certain themes. It originated from information/library science but has been applied in various disciplines, including information science, library science, natural science, technology, engineering, medical sciences, and social sciences and humanities. Numerous scientometric studies have been carried out, but no study has attempted to investigate the overall research status of scientometrics. The objective of this study was to investigate the research status of scientometrics based on 16,225 publications archived in the Web of Science Core Collection between 1992 and 2020. The results show that there has been a marked increase in publications on scientometric studies over the past decades, with “Information Science Library Science” being the predominant discipline publishing scientometric studies, but scientometrics has been widely adopted in a variety of other disciplines (240 of 254 Web of Science categories). It was found that Web of Science, Vosviewer, and Scientometrics are the most utilized database, software, and journal for scientometric studies, respectively. The most productive author (Lutz Bornmann from the Max Planck Society, Germany), organization (University of Granada, Spain), and country (USA) are also identified. In addition, high-impact scientometric studies and the research landscape are analyzed through citation networks and the co-occurrence of keywords method.}, language = {en}, number = {12}, urldate = {2024-06-21}, journal = {Information}, author = {Liu, Yang and He, Hailong}, month = nov, year = {2023}, pages = {637}, file = {Liu et He - 2023 - Scientometrics of Scientometrics Based on Web of S.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\I7R6I389\\Liu et He - 2023 - Scientometrics of Scientometrics Based on Web of S.pdf:application/pdf}, } @article{alsolbi_different_2022, title = {Different approaches of bibliometric analysis for data analytics applications in non-profit organisations}, volume = {2}, issn = {27676595}, url = {https://www.oaepublish.com/articles/jsegc.2022.09}, doi = {10.20517/jsegc.2022.09}, abstract = {Aim: Profitable companies that used data analytics have a double gain in cost reduction, demand prediction, and decision-making. However, using data analysis in non-profit organisations (NPOs) can help understand and identify more patterns of donors, volunteers, and anticipated future cash, gifts, and grants. This article presents a bibliometric study of 2673 to discover the use of data analytics in different NPOs and understand its contribution.}, language = {en}, number = {3}, urldate = {2024-06-21}, journal = {Journal of Smart Environments and Green Computing}, author = {Alsolbi, Idrees and Wu, Mengjia and Zhang, Yi and Joshi, Sudhanshu and Sharma, Manu and Tafavogh, Siamak and Sinha, Ashish and Prasad, Mukesh}, year = {2022}, pages = {90--104}, file = {Alsolbi et al. - 2022 - Different approaches of bibliometric analysis for .pdf:C\:\\Users\\guillemi\\Zotero\\storage\\ZW9AEKMD\\Alsolbi et al. - 2022 - Different approaches of bibliometric analysis for .pdf:application/pdf}, } @article{van_raan_bibliometrics_2010, title = {Bibliometrics: {Measure} for measure}, volume = {468}, copyright = {http://www.springer.com/tdm}, issn = {0028-0836, 1476-4687}, shorttitle = {Bibliometrics}, url = {https://www.nature.com/articles/468763a}, doi = {10.1038/468763a}, language = {en}, number = {7325}, urldate = {2024-06-21}, journal = {Nature}, author = {Van Raan, Ton}, month = dec, year = {2010}, pages = {763--763}, file = {Van Raan - 2010 - Bibliometrics Measure for measure.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\L7NMLB64\\Van Raan - 2010 - Bibliometrics Measure for measure.pdf:application/pdf}, } @article{lyu_bibliometric_2023, title = {A bibliometric analysis of literature on bibliometrics in recent half-century}, issn = {0165-5515}, doi = {10.1177/01655515231191233}, abstract = {Bibliometrics research has been developed for many years and achieved a great many scientific achievements. The aim of this study is to understand the current research status and development directions of research on bibliometrics. This study implements bibliometric methods based on the Web of Science to analyse the publications, subjects, citation, co-citation, collaboration and keywords of bibliometrics from 1969 to 2022. Bibliometrics is now in the development phase from its cumulative publication curve and citation analysis. Information Science \& Library Science and Computer Science are the two major subjects on bibliometric research. Garfield E has the most citations and co-citation frequency in the field of bibliometrics. The number of countries cooperating with the United States is the largest and China is the most productive country; Beijing, London and Madrid are the three sub-network centres of the city cooperation network; Zhang L owns the largest number of author collaborations. Research content on bibliometrics focuses mainly on bibliometrics theory, methods, research evaluation, techniques, tools and applications. The results in this study are beneficial to researchers and readers who are interested in the field of bibliometrics and other related fields to understand the overall picture of bibliometrics, which is conducive to the future development of bibliometrics.}, journal = {JOURNAL OF INFORMATION SCIENCE}, author = {Lyu, P and Liu, XL and Yao, T}, month = aug, year = {2023}, file = {Lyu et al. - 2023 - A bibliometric analysis of literature on bibliomet.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\RP6CJKNE\\Lyu et al. - 2023 - A bibliometric analysis of literature on bibliomet.pdf:application/pdf}, } @article{torres-salinas_bibliometric_2023, title = {The bibliometric journey towards technological and social change: {A} review of current challenges and issues}, volume = {32}, issn = {1386-6710}, doi = {10.3145/epi.2023.mar.28}, abstract = {The current trends and challenges in the field of bibliometrics are reviewed. To do so, we take the reader along a bibliometric route with six stations: the explosion of databases, the inflation of metrics, its relationship to Data Science, searching for meaning, evaluative bibliometrics, and diversity and profession. This evaluation encompasses three dimensions of the bibliometrics field regarding research evaluation: the technological, the theoretical, and the social. Finally, we advocate for the principles of an evaluative bibliometrics, balancing the power of metrics with expert judgment and science policy.}, number = {2}, journal = {PROFESIONAL DE LA INFORMACION}, author = {Torres-Salinas, D and Robinson-García, N and Jiménez-Contreras, E}, year = {2023}, keywords = {Scientific databases, IMPACT, Bibliometric indicators, Evaluative bibliometrics, Evolution, INDICATORS, Metrics, METRICS, Peer review, POLICY, Research evaluation, SCHOLARLY DATA, Trends}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  91}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  91}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\K2TMN6YR\\Torres-Salinas et al. - 2023 - The bibliometric journey towards technological and.pdf:application/pdf}, } @article{chiu_editorial_2024, title = {Editorial: {Special} selection on current bibliometrics and reviews}, volume = {42}, issn = {0737-8831}, doi = {10.1108/LHT-02-2024-591}, number = {1}, journal = {LIBRARY HI TECH}, author = {Chiu, DKW and Ho, KKW}, month = feb, year = {2024}, pages = {1--7}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\UM8ZLU68\\Chiu et Ho - 2024 - Editorial Special selection on current bibliometr.pdf:application/pdf}, } @article{rahman_workshop_2024, title = {Workshop report: 28th {Nordic} workshop on bibliometrics and research policy, {October} 11-13, 2023, {Gothenburg}, {Sweden}}, volume = {29}, issn = {1368-1613}, doi = {10.47989/ir291750}, abstract = {The Nordic workshop on bibliometrics and research policy has been an annual event for almost three decades, rotating between the Nordic countries. It is a forum for the bibliometrics community to discuss contemporary research practices and policies. The 28th edition of the workshop took place in Gothenburg, Sweden. Featuring 27 oral and 15 poster presentations authored by 104 individuals, this event attracted 119 attendees from 19 countries. The event helped the participants to enhance their knowledge and engage with their peers. This workshop report offers insights into the pre -workshop sessions and provides an overview of the oral presentations across eight thematic sessions, keynote speeches, panel discussions, and poster sessions. Additionally, it includes references with links to presentations, posters, the book of abstracts, recording of keynote speeches and panel discussion.}, number = {1}, journal = {INFORMATION RESEARCH-AN INTERNATIONAL ELECTRONIC JOURNAL}, author = {Rahman, AIMJ and Schirone, M and Friberg, PA and Granell, C}, month = mar, year = {2024}, pages = {147--157}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\BPU2NH32\\Rahman et al. - 2024 - Workshop report 28th Nordic workshop on bibliomet.pdf:application/pdf}, } @article{fassin_notion_2023, title = {The notion of dominant terminology in bibliometric research}, volume = {8}, issn = {2096-157X}, doi = {10.2478/jdis-2023-0020}, abstract = {In this opinion paper, we introduce the expressions of dominant terminology and dominant term in the quantitative studies of science in analogy to the notion of dominant design in product development and innovation.}, number = {4}, journal = {JOURNAL OF DATA AND INFORMATION SCIENCE}, author = {Fassin, Y and Rousseau, R}, month = nov, year = {2023}, pages = {1--7}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\7YCI87ST\\Fassin et Rousseau - 2023 - The notion of dominant terminology in bibliometric.pdf:application/pdf}, } @article{burrell_exploring_2024, title = {Exploring the relationship between traditional bibliometrics and {Altmetric} scores in the primary care literature}, volume = {37}, issn = {0953-1513}, doi = {10.1002/leap.1584}, abstract = {There is some evidence that Altmetric scores correlate with citations in medical research, but this is not consistent across different specialties. No previous studies have examined the association between Altmetric score and citations amongst primary care research journals. The aim of this study was therefore to describe this association. We identified the ten most frequently cited articles published in the top 15 highest impact factor primary care research journals. Article and journal metrics were extracted and summarized using descriptive statistics. We used Spearman's correlation coefficient (rs) and log-log linear regression modelling to examine the relationship between citations and Altmetric score. 150 articles were included with a median of 36.5 (IQR 20-59; range 5-811) citations. We found a positive association between citations and Altmetric score (rs = 0.519; p {\textless} 0.001). A unit increase in log Altmetric score was associated with increased log citations [0.175 (95\% CI 0.091-0.259, p {\textless} 0.001)] in an adjusted linear regression model. The regression findings indicate that increasing Altmetric score by 10\% was associated with a 1.68\% increase in citation rate. This has implications for how authors, academic institutions and primary care research journals approach dissemination of articles.}, number = {2}, journal = {LEARNED PUBLISHING}, author = {Burrell, A and Butler, D and Ukoumunne, OC and Dambha-Miller, H}, month = apr, year = {2024}, pages = {109--116}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\6XLQYF4F\\Burrell et al. - 2024 - Exploring the relationship between traditional bib.pdf:application/pdf}, } @article{guskov_challenges_2023, title = {Challenges to develop scientometric studies}, issn = {0130-9765}, doi = {10.33186/1027-3689-2023-2-37-58}, abstract = {The authors examine the key problems inhibiting scientometric studies and scientific communications. These challenges call for significant efforts and professional courage. Firstly, this is the need for open access to scientometric data and improvement of their quality and comprehensiveness, including author data, affiliations, citations and meta information. The authors emphasize the necessity for large-scale introduction of technologies for identifying objects of science information (i. e. publications, researchers, organizations, projects, etc.), which would enable to decrease significantly the number of bibliographic mistakes. When projecting scientometric studies, the edge of objects and analysis instruments have to be defined by the goals rather than by bibliometric database limitations. Indexing of scientific publications is among the key instruments. Its advancement is determined by emerging and low-quality classifications of bibliometric databases, their differences, and changing science structure. Finally, the propriety of scientometric methods and results interpretation, in particular that of scientometric performance assessment, have to be controlled. Meeting these challenges will enable to provide efficient monitoring of scientific activity based on operative collection, processing and analysis of scientific information flows rather than on annual statistical surveys. This transfer would improve monitoring significantly and expand the spectrum of solutions; it would also enable to reveal system changes in research, to respond to disparities in development, and to make the solutions in science management more efficient.}, number = {2}, journal = {NAUCHNYE I TEKHNICHESKIE BIBLIOTEKI-SCIENTIFIC AND TECHNICAL LIBRARIES}, author = {Guskov, AE and Shrayberg, YL}, year = {2023}, pages = {37--58}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\RC7DB5WS\\Guskov et Shrayberg - 2023 - Challenges to develop scientometric studies.pdf:application/pdf}, } @article{momeni_which_2023, title = {Which factors are associated with {Open} {Access} publishing? {A} {Springer} {Nature} case study}, volume = {4}, issn = {2641-3337}, doi = {10.1162/qss_a_00253}, abstract = {Open Access (OA) facilitates access to research articles. However, authors or funders often must pay the publishing costs, preventing authors who do not receive financial support from participating in OA publishing and gaining citation advantage for OA articles. OA may exacerbate existing inequalities in the publication system rather than overcome them. To investigate this, we studied 522,411 articles published by Springer Nature. Employing correlation and regression analyses, we describe the relationship between authors affiliated with countries from different income levels, their choice of publishing model, and the citation impact of their papers. A machine learning classification method helped us to explore the importance of different features in predicting the publishing model. The results show that authors eligible for article processing charge (APC) waivers publish more in gold OA journals than others. In contrast, authors eligible for an APC discount have the lowest ratio of OA publications, leading to the assumption that this discount insufficiently motivates authors to publish in gold OA journals. We found a strong correlation between the journal rank and the publishing model in gold OA journals, whereas the OA option is mostly avoided in hybrid journals. Also, results show that the countries' income level, seniority, and experience with OA publications are the most predictive factors for OA publishing in hybrid journals.}, number = {2}, journal = {QUANTITATIVE SCIENCE STUDIES}, author = {Momeni, F and Dietze, S and Mayr, P and Biesenbender, K and Peters, I}, month = may, year = {2023}, pages = {353--371}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\7RUU43IP\\Momeni et al. - 2023 - Which factors are associated with Open Access publ.pdf:application/pdf}, } @article{fassin_ha-index_2023, title = {The ha-index: {The} average citation h-index}, volume = {4}, issn = {2641-3337}, doi = {10.1162/qss_a_00259}, abstract = {The ranking and categorizations of academic articles of a data set have traditionally been based on the distribution of their total citations. This ranking formed the basis for the definition of the h-index. As an alternative methodology, the ranking of articles of a data set can be performed according to the distribution of the average citations of the articles. Applying this same principle to the h-index itself leads to an average h-index, the ha-index: the largest number of papers ha published by a researcher who has obtained at least ha citations per year on average. The new ha-index offers more consistency, increased selectivity, and fairer treatment of younger scholars compared to the classic h-index. With its normalized time aspect, the method leads to better acknowledgment of progress. The evolution of the h-indices over time shows how the ha-index reaches its full potential earlier and offers more stability over time. The average citation ha-index partly solves the problem of the temporality of the h-index. he ha-index can also be applied to academic journals. In particular, the application of the ha-index to journals leads to more stability as they reach their limit sooner. The ha-index offers a response to the inflation of h-index levels.}, number = {3}, journal = {QUANTITATIVE SCIENCE STUDIES}, author = {Fassin, Y}, month = dec, year = {2023}, pages = {756--777}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\MDJUBFHV\\Fassin - 2023 - The ha-index The average citation h-index.pdf:application/pdf}, } @article{vakkari_what_2024, title = {What characterizes {LIS} as a fragmenting discipline?}, volume = {80}, issn = {0022-0418}, doi = {10.1108/JD-10-2023-0207}, abstract = {PurposeThe purpose of this paper is to characterize library and information science (LIS) as fragmenting discipline both historically and by applying Whitley's (1984) theory about the organization of sciences and Fuchs' (1993) theory about scientific change.Design/methodology/approachThe study combines historical source analysis with conceptual and theoretical analysis for characterizing LIS. An attempt is made to empirically validate the distinction between LIS context, L\&I services and information seeking as fragmented adhocracies and information retrieval and scientific communication (scientometrics) as technologically integrated bureaucracies.FindingsThe origin of fragmentation in LIS due the contributions of other disciplines can be traced in the 1960s and 1970s for solving the problems produced by the growth of scientific literature. Computer science and business established academic programs and started research relevant to LIS community focusing on information retrieval and bibliometrics. This has led to differing research interests between LIS and other disciplines concerning research topics and methods. LIS has been characterized as fragmented adhocracy as a whole, but we make a distinction between research topics LIS context, L\&I services and information seeking as fragmented adhocracies and information retrieval and scientific communication (scientometrics) as technologically integrated bureaucracies.Originality/valueThe paper provides an elaborated historical perspective on the fragmentation of LIS in the pressure of other disciplines. It also characterizes LIS as discipline in a fresh way by applying Whitley's (1984) theory.}, number = {7}, journal = {JOURNAL OF DOCUMENTATION}, author = {Vakkari, P}, month = feb, year = {2024}, pages = {60--77}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\AK48RU72\\Vakkari - 2024 - What characterizes LIS as a fragmenting discipline.pdf:application/pdf}, } @article{castanha_convergence_2023, title = {Convergence culture: an analysis based on bibliometric indicators of production, citation and relational co-citation of authors in the {Web} of {Science} database (2008-2021)}, volume = {29}, issn = {1807-8893}, doi = {10.19132/1808-5245.29.122198}, abstract = {This research analyzes the scientific production related to convergence culture through bibliometric indicators of production, citation and relational co-citation. Specifically, it evaluates scientific production using production and citation indicators, and characterizes the main influencers on the recovered work through the analysis of co-citation between authors. For this, it searches for the term convergence culture in the Web of Science database and evaluates the production of articles over the years together with the citations received and reveals, through the analysis of co-citation between authors, the main influencers on the retrieved work. To analyze the co-citations, it uses the concept of diachronic recitations of authors per document to build the intellectual structure of the domain in question. As a result, it presents a low productivity of articles close to saturation, 34\% of the articles without citations received and with a clear deceleration of citations per article. It illustrates that the intellectual structure of the theme is composed of 46 authors most cited in the entire work, with emphasis on Henry Jenkins, Scolari, Williams, Bruns, Couldry, Deuze, Carpentier and Andrejevier. It concludes with low productivity on the subject and with strong influences from the pioneer Henry Jenkins, who is the most cited, recited and co-cited author among all cited authors.}, journal = {EM QUESTAO}, author = {Castanha, RG and dos Santos Junior, EA and Tolare, JB}, year = {2023}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\T5FEZQ8N\\Castanha et al. - 2023 - Convergence culture an analysis based on bibliome.pdf:application/pdf}, } @article{ferreira_systematization_2023, title = {Systematization of obtaining thematic indicators of scientific information}, volume = {28}, issn = {1518-2924}, doi = {10.5007/1518-2924.2023.e92070}, abstract = {Objective: In the context of the development of information metric studies, this article proposes and applies a method for obtaining thematic indicators on descriptors representative of themes, subjects or keywords addressed in bibliographic records in the Information Science area. Method: A methodological research of applied nature was carried out, using technical procedures of automatic indexing and information metric studies. Initially, a corpus was delimited contemplating a set of bibliographic records referring to 60 articles of Brazilian journals. Later, the software Maui was applied as an automatic indexing system for categorizing the keywords of the bibliographic records into concepts of a specialty thesaurus, contemplating descriptors in the language of the metadata text. Next, the Iramuteq software was applied to generate the thematic indicators from the descriptors obtained by the automatic indexing. Finally, the proposed method was validated based on the analysis of the results obtained for the corpus. Result: The flowcharts for validation of automatic indexing and for validation of the information metric study are described, aiming to explain the processes of the proposed method as steps in processing the corpus. In addition, quality metrics for automatic indexing are presented, as well as statistical analyses of word frequency and co-occurrence, and term frequency, where the corpus' main thematic indicators are pointed out. Conclusions: We conclude that the thematic indicators obtained by applying the proposed method represent the main themes identified in the corpus, and that the method can be applied to obtain thematic indicators for other sets of bibliographic records.}, journal = {ENCONTROS BIBLI-REVISTA ELETRONICA DE BIBLIOTECONOMIA E CIENCIA DA INFORMACAO}, author = {Ferreira, MHW and Correa, RF}, year = {2023}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\W2T7SKMB\\Ferreira et Correa - 2023 - Systematization of obtaining thematic indicators o.pdf:application/pdf}, } @article{leibel_what_2024, title = {What do we know about the disruption index in scientometrics? {An} overview of the literature}, volume = {129}, issn = {0138-9130}, doi = {10.1007/s11192-023-04873-5}, abstract = {The purpose of this paper is to provide a review of the literature on the original disruption index (DI1) and its variants in scientometrics. The DI1 has received much media attention and prompted a public debate about science policy implications, since a study published in Nature found that papers in all disciplines and patents are becoming less disruptive over time. This review explains in the first part the DI1 and its variants in detail by examining their technical and theoretical properties. The remaining parts of the review are devoted to studies that examine the validity and the limitations of the indices. Particular focus is placed on (1) possible biases that affect disruption indices (2) the convergent and predictive validity of disruption scores, and (3) the comparative performance of the DI1 and its variants. The review shows that, while the literature on convergent validity is not entirely conclusive, it is clear that some modified index variants, in particular DI5, show higher degrees of convergent validity than DI1. The literature draws attention to the fact that (some) disruption indices suffer from inconsistency, time-sensitive biases, and several data-induced biases. The limitations of disruption indices are highlighted and best practice guidelines are provided. The review encourages users of the index to inform about the variety of DI1 variants and to apply the most appropriate variant. More research on the validity of disruption scores as well as a more precise understanding of disruption as a theoretical construct is needed before the indices can be used in the research evaluation practice.}, number = {1}, journal = {SCIENTOMETRICS}, author = {Leibel, C and Bornmann, L}, month = jan, year = {2024}, pages = {601--639}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\YHNITPLR\\Leibel et Bornmann - 2024 - What do we know about the disruption index in scie.pdf:application/pdf}, } @article{orduna-malea_crossing_2020, title = {Crossing the academic ocean? {Judit} {Bar}-{Ilan}'s oeuvre on search engines studies}, volume = {123}, issn = {0138-9130}, doi = {10.1007/s11192-020-03450-4}, abstract = {The main objective of this work is to analyse the contributions of Judit Bar-Ilan to the search engines studies. To do this, two complementary approaches have been carried out. First, a systematic literature review of 47 publications authored and co-authored by Judit and devoted to this topic. Second, an interdisciplinarity analysis based on the cited references (publications cited by Judit) and citing documents (publications that cite Judit's work) through Scopus. The systematic literature review unravels an immense amount of search engines studied (43) and indicators measured (especially technical precision, overlap and fluctuation over time). In addition to this, an evolution over the years is detected from descriptive statistical studies towards empirical user studies, with a mixture of quantitative and qualitative methods. Otherwise, the interdisciplinary analysis evidences that a significant portion of Judit's oeuvre was intellectually founded on the computer sciences, achieving a significant, but not exclusively, impact on library and information sciences.}, number = {3}, journal = {SCIENTOMETRICS}, author = {Orduña-Malea, E}, month = jun, year = {2020}, pages = {1317--1340}, file = {Version soumise:C\:\\Users\\guillemi\\Zotero\\storage\\6BUK42WX\\Orduña-Malea - 2020 - Crossing the academic ocean Judit Bar-Ilan's oeuv.pdf:application/pdf}, } @article{lewison_preparation_2020, title = {Preparation of bibliometrics papers}, volume = {92}, copyright = {http://creativecommons.org/licenses/by/4.0/}, issn = {1678-2690, 0001-3765}, url = {http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652020000500201&tlng=en}, doi = {10.1590/0001-3765202020201327}, abstract = {Suggestions are made on how to write papers on bibliometrics. Key words: Bibliometrics, guidelines, citations, normalisation.}, language = {en}, number = {3}, urldate = {2024-08-01}, journal = {Anais da Academia Brasileira de Ciências}, author = {Lewison, Grant}, year = {2020}, keywords = {Bibliometrics, citations, guidelines, normalisation}, pages = {e20201327}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  1}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  1}, file = {Lewison - 2020 - Preparation of bibliometrics papers.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\JS6A8MYR\\Lewison - 2020 - Preparation of bibliometrics papers.pdf:application/pdf}, } @article{bertin_invariant_2016, title = {The invariant distribution of references in scientific articles}, volume = {67}, copyright = {http://onlinelibrary.wiley.com/termsAndConditions\#vor}, issn = {2330-1635, 2330-1643}, url = {https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.23367}, doi = {10.1002/asi.23367}, abstract = {The organization of scientific papers typically follows a standardized pattern, the well‐known IMRaD structure (introduction, methods, results, and discussion). Using the full text of 45,000 papers published in the PLoS series of journals as a case study, this paper investigates, from the viewpoint of bibliometrics, how references are distributed along the structure of scientific papers as well as the age of these cited references. Once the sections of articles are realigned to follow the IMRaD sequence, the position of cited references along the text of articles is invariant across all PLoS journals, with the introduction and discussion accounting for most of the references. It also provides evidence that the age of cited references varies by section, with older references being found in the methods and more recent references in the discussion. These results provide insight into the different roles citations have in the scholarly communication process.}, language = {en}, number = {1}, urldate = {2024-08-05}, journal = {Journal of the Association for Information Science and Technology}, author = {Bertin, Marc and Atanassova, Iana and Gingras, Yves and Larivière, Vincent}, month = jan, year = {2016}, pages = {164--177}, file = {Bertin et al. - 2016 - The invariant distribution of references in scient.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\LAYGCN9S\\Bertin et al. - 2016 - The invariant distribution of references in scient.pdf:application/pdf}, } @article{bornmann_bibliometrics-based_2020, title = {Bibliometrics-based decision trees ({BBDTs}) based on bibliometrics-based heuristics ({BBHs}): {Visualized} guidelines for the use of bibliometrics in research evaluation}, volume = {1}, issn = {2641-3337}, doi = {10.1162/qss_a_00012}, abstract = {Fast-and-frugal heuristics are simple strategies that base decisions on only a few predictor variables. In so doing, heuristics may not only reduce complexity but also boost the accuracy of decisions, their speed, and transparency. In this paper, bibliometrics-based decision trees (BBDTs) are introduced for research evaluation purposes. BBDTs visualize bibliometrics-based heuristics (BBHs), which are judgment strategies solely using publication and citation data. The BBDT exemplar presented in this paper can be used as guidance to find an answer on the question in which situations simple indicators such as mean citation rates are reasonable and in which situations more elaborated indicators (i.e., [sub-]field-normalized indicators) should be applied.}, language = {English}, number = {1}, journal = {QUANTITATIVE SCIENCE STUDIES}, author = {Bornmann, L}, year = {2020}, keywords = {bibliometrics, bibliometrics-based decision tree (BBDT), bibliometrics-based heuristic (BBH), CITATION IMPACT, FRUGAL, heuristics, MODELS, NORMALIZATION}, pages = {171--182}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  53}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  53}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\W5NJ26FI\\Bornmann - 2020 - Bibliometrics-based decision trees (BBDTs) based o.pdf:application/pdf}, } @article{pallis_look_2019, title = {A {Look} at the {Bibliometrics}}, volume = {23}, issn = {1089-7801}, doi = {10.1109/MIC.2019.2931020}, language = {English}, number = {4}, journal = {IEEE INTERNET COMPUTING}, author = {Pallis, G}, month = jul, year = {2019}, keywords = {Bibliometrics}, pages = {5--7}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  0}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  0}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\QQPCGVJK\\Pallis - 2019 - A Look at the Bibliometrics.pdf:application/pdf}, } @article{ninkov_bibliometrics_2022, title = {Bibliometrics: {Methods} for studying academic publishing}, volume = {11}, issn = {2212-2761}, doi = {10.1007/s40037-021-00695-4}, abstract = {Bibliometrics is the study of academic publishing that uses statistics to describe publishing trends and to highlight relationships between published works. Likened to epidemiology, researchers seek to answer questions about a field based on data about publications (e.g., authors, topics, funding) in the same way that an epidemiologist queries patient data to understand the health of a population. In this Eye Opener, the authors introduce bibliometrics and define its key terminology and concepts, including relational and evaluative bibliometrics. Readers are introduced to common bibliometric methods and their related strengths and weaknesses. The authors provide examples of bibliometrics applied in health professions education and propose potential future research directions. Health professions educators are consumers of bibliometric reports and can adopt its methodologies for future studies.}, language = {English}, number = {3}, journal = {PERSPECTIVES ON MEDICAL EDUCATION}, author = {Ninkov, A and Frank, JR and Maggio, LA}, month = jun, year = {2022}, keywords = {Bibliometrics, Information science, Scholarly communication}, pages = {173--176}, annote = {Times Cited in Web of Science Core Collection:  188Total Times Cited:  193Cited Reference Count:  24}, annote = {Times Cited in Web of Science Core Collection:  188Total Times Cited:  193Cited Reference Count:  24}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\V4SBE9R9\\Ninkov et al. - 2022 - Bibliometrics Methods for studying academic publi.pdf:application/pdf}, } @article{yilmaz_critical_2019, title = {A {Critical} {View} on {Bibliometrics}}, volume = {33}, issn = {1300-0039}, doi = {10.24146/tkd.2019.47}, abstract = {Bibliometrics is both a research area determining the distribution of the information produced quantitatively by various factors and a research method. The aim of this study is to examine bibliometrics as a scientific discipline with a critical approach. In this context, the hypothesis of our study is as follows; "In assessing the productivity of research and researcher, bibliometric studies give more weight to quantitative aspects of the productivity. However, the productivity of research and researcher should not be determined only by quantitative aspects". In this study, our criticisms about bibliometrics and bibliometric studies are listed as follows: Terminological problems about bibliometrics Problems related to the importance given to quantity Technical and interpretative problems arising from authors, and Technical problems related to databases involving the related literature. This study has demonstrated that the only quantitative aspects are not sufficient to assess the productivity of research and researcher.}, language = {Turkish}, number = {1}, journal = {TURKISH LIBRARIANSHIP}, author = {Yilmaz, M}, year = {2019}, keywords = {Bibliometrics, author productivity, informetrics, quality, quantity, research productivity}, pages = {43--49}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  13}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  13}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\LIDYTZTM\\Yilmaz - 2019 - A Critical View on Bibliometrics.pdf:application/pdf}, } @article{kruger_i_2023, title = {'{I} want to be able to do what {I} know the tools will allow us to do': {Practicing} evaluative bibliometrics through digital infrastructure}, volume = {31}, issn = {0958-2029}, doi = {10.1093/reseval/rvac009}, abstract = {The proliferation of quantitative research assessment has been accompanied by an increasing growth and diversification of digital infrastructure for evaluative bibliometrics. Since the beginning of the 2000s, insights into academic performance provided by a variety of new databases and devices significantly exceed the capacities of the former Science Citation Index and embedded metrics. Going beyond the research on the construction, uses, and consequences of bibliometric indicators, we therefore posit that a perspective on bibliometric infrastructure is crucial for understanding how evaluative bibliometrics is put into practice. Drawing on interviews with academic librarians on the increasing provision and implementation of bibliometric infrastructure in the years 2013 and 2014, we analyse how the entanglement of technology and its users shapes how evaluative bibliometrics is understood and practiced.}, language = {English}, number = {4}, journal = {RESEARCH EVALUATION}, author = {Krüger, AK and Petersohn, S}, month = feb, year = {2023}, keywords = {academic libraries, ACCESS, analytic software tools, citation databases, CITIZEN BIBLIOMETRICS, current research information systems, DESIGN, DEVICES, digital infrastructure, DIMENSIONS, evaluative bibliometrics, SCIENCE, SOCIOLOGY, SYSTEM, T INDICATORS}, pages = {475--485}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  80}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  80}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\ELF4WULL\\Krüger et Petersohn - 2023 - 'I want to be able to do what I know the tools wil.pdf:application/pdf}, } @article{orduna-malea_next_2016, title = {{THE} {NEXT} {BIBLIOMETRICS}: {ALMETRICS} ({AUTHOR} {LEVEL} {METRICS}) {AND} {THE} {MULTIPLE} {FACES} {OF} {AUTHOR} {IMPACT}}, volume = {25}, issn = {1386-6710}, doi = {10.3145/epi.2016.may.18}, abstract = {The main goal of this article is to describe the purpose and content of a new branch of bibliometrics: ALMetrics (Author-Level Metrics). ALMetrics is focused on the quantitative analysis of an author's performance by measuring the dimensions of their intellectual activity as shown through varied metric indicators. This article will list, define, and classify the different metrics that are offered in newer information portals that showcase the scientific activity of authors. These metrics are grouped into five sets: bibliometrics (publication and citation), usage, participation, rating, social connectivity, and composite indicators. This new bibliometric specialty is necessary because of new trends in scientific assessment, which have moved analysis away from old bibliometrics (based on journal analysis and Impact Factor) towards new bibliometrics that analyze both documents and authors via a mix of indicators. Most importantly, ALMetrics responds to the researchers' desire for both knowledge and acknowledgement.}, language = {English}, number = {3}, journal = {PROFESIONAL DE LA INFORMACION}, author = {Orduña-Malea, E and Martín-Martín, A and Delgado-López-Cózar, E}, month = may, year = {2016}, keywords = {Bibliometrics, Altmetrics, INDICATORS, ALMetrics, Author-level metrics, Scientific evaluation, Social academic networks}, pages = {485--496}, annote = {Times Cited in Web of Science Core Collection:  24Total Times Cited:  30Cited Reference Count:  24}, annote = {Times Cited in Web of Science Core Collection:  24Total Times Cited:  30Cited Reference Count:  24}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\VUDG22SG\\Orduña-Malea et al. - 2016 - THE NEXT BIBLIOMETRICS ALMETRICS (AUTHOR LEVEL ME.pdf:application/pdf}, } @article{guler_scientific_2016, title = {Scientific workflows for bibliometrics}, volume = {107}, issn = {0138-9130}, doi = {10.1007/s11192-016-1885-6}, abstract = {Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly available through the myExperiment community and then used in other workflows. We here illustrate how scientific workflows and the Taverna workbench in particular can be used in bibliometrics. We discuss the specific capabilities of Taverna that makes this software a powerful tool in this field, such as automated data import via Web services, data extraction from XML by XPaths, and statistical analysis and visualization with R. The support of the latter is particularly relevant, as it allows integration of a number of recently developed R packages specifically for bibliometrics. Examples are used to illustrate the possibilities of Taverna in the fields of bibliometrics and scientometrics.}, language = {English}, number = {2}, journal = {SCIENTOMETRICS}, author = {Guler, AT and Waaijer, CJF and Palmblad, M}, month = may, year = {2016}, keywords = {Bibliometrics, BIOINFORMATICS, Mass spectrometry, Medicinal chemistry, R, R PACKAGE, Scientific workflows, Taverna, TAVERNA, XML}, pages = {385--398}, annote = {Times Cited in Web of Science Core Collection:  122Total Times Cited:  126Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  122Total Times Cited:  126Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  122Total Times Cited:  126Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  122Total Times Cited:  126Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  122Total Times Cited:  126Cited Reference Count:  21}, file = {Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\PW5L47B7\\Guler et al. - 2016 - Scientific workflows for bibliometrics.pdf:application/pdf}, } @article{rahman_comprehensive_2022, title = {A {Comprehensive} {Survey} on {Affinity} {Analysis}, {Bibliomining}, and {Technology} {Mining}: {Past}, {Present}, and {Future} {Research}}, volume = {12}, issn = {2076-3417}, doi = {10.3390/app12105227}, abstract = {Recent advancements in high-speed communications and high-capacity computing systems have contributed to major growth in the data volume of databases. Data mining is a crucial part of information retrieval; it is often termed as database knowledge discovery. It consists of techniques for examining massive data sets, to find hidden (but possibly important) information. Three interesting fields in data mining are affinity analysis, bibliomining, and technology mining. Affinity analysis provides data mining techniques to determine the similarity among objects; bibliomining is a combination of data mining, bibliometrics, and data warehousing; technology mining is a research topic that is an obstacle to many scientists in the fields of time association, enterprise association, and computer programming. We present a systematic review of the notable research articles in the fields of affinity analysis, bibliomining, and technology mining published between 2000 and December 2021. We provide a systematic analysis of the selected literature by specifying the major contributions, used data sets, performance evaluations, and limitations. Our findings demonstrate that affinity analysis interoperability extends well beyond market basket analysis. We also demonstrate that, in the age of big data, the personalized needs of users are the driving forces behind the evolution of the digital library from a resource-sharing service to a user-centered service. Finally, this article provides insight into major advances and outstanding challenges in the fields of affinity analysis, bibliomining, and technology mining.}, language = {English}, number = {10}, journal = {APPLIED SCIENCES-BASEL}, author = {Rahman, MR and Arefin, MS and Rahman, S and Ahmed, A and Islam, T and Dhar, PK and Kwon, OJ}, month = may, year = {2022}, keywords = {ACQUISITION BUDGET ALLOCATION, affinity analysis, ALGORITHM, association mining, ASSOCIATION RULES, BIBLIOMETRICS, bibliomining, correlation mining, SUPPORT, technology mining, WEIGHTED INTERESTING PATTERNS}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  97}, file = {1-s2.0-S0099133321000884-main.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\5VLY8TH7\\1-s2.0-S0099133321000884-main.pdf:application/pdf;Texte intégral:C\:\\Users\\guillemi\\Zotero\\storage\\6ES3RSMQ\\Rahman et al. - 2022 - A Comprehensive Survey on Affinity Analysis, Bibli.pdf:application/pdf}, } @article{morris_diva_2002, title = {{DIVA}: a visualization system for exploring document databases for technology forecasting}, volume = {43}, issn = {0360-8352}, doi = {10.1016/S0360-8352(02)00143-2}, abstract = {Database Information Visualization and Analysis system (DIVA) is a computer program that helps perform bibliometric analysis of collections of scientific literature and patents for technology forecasting. Documents, drawn from the technological field of interest, are visualized as clusters on a two dimensional map, permitting exploration of the relationships among the documents and document clusters and also permitting derivation of summary data about each document cluster. Such information, when provided to subject matter experts performing a technology forecast, can yield insight into trends in the technological field of interest. This paper discusses the document visualization and analysis process: acquisition of documents, mapping documents, clustering, exploration of relationships, and generation of summary and trend information. Detailed discussion of DIVA exploration functions is presented and followed by an example of visualization and analysis of a set of documents about chemical sensors. (C) 2002 Published by Elsevier Science Ltd.}, language = {English}, number = {4}, journal = {COMPUTERS \& INDUSTRIAL ENGINEERING}, author = {Morris, S and DeYong, C and Wu, Z and Salman, S and Yemenu, D}, month = sep, year = {2002}, keywords = {bibliometrics, data mining, knowledge discovery in databases, citation analysis, document mapping, information visualization, KDD, scientometrics, technology forecasting}, pages = {841--862}, annote = {Times Cited in Web of Science Core Collection:  90Total Times Cited:  103Cited Reference Count:  13}, annote = {Times Cited in Web of Science Core Collection:  90Total Times Cited:  103Cited Reference Count:  13}, annote = {Times Cited in Web of Science Core Collection:  90Total Times Cited:  103Cited Reference Count:  13}, annote = {Times Cited in Web of Science Core Collection:  90Total Times Cited:  103Cited Reference Count:  13}, } @article{godin_origins_2006, title = {On the origins of bibliometrics}, volume = {68}, copyright = {http://www.springer.com/tdm}, issn = {0138-9130, 1588-2861}, url = {http://link.springer.com/10.1007/s11192-006-0086-0}, doi = {10.1007/s11192-006-0086-0}, language = {en}, number = {1}, urldate = {2024-08-14}, journal = {Scientometrics}, author = {Godin, Benoît}, month = jul, year = {2006}, keywords = {SCIENCE, AGE, AMERICAN-PSYCHOLOGICAL-ASSOCIATION, ARTICLES, DIFFERENT LANGUAGES, NUMBER, PERFORMANCE, SCIENTIFIC PRODUCTIVITY, UNITED-STATES, VITAL-STATISTICS}, pages = {109--133}, annote = {Times Cited in Web of Science Core Collection:  158Total Times Cited:  174Cited Reference Count:  153}, annote = {Times Cited in Web of Science Core Collection:  158Total Times Cited:  174Cited Reference Count:  153}, file = {Godin - 2006 - On the origins of bibliometrics.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\KAFNME63\\Godin - 2006 - On the origins of bibliometrics.pdf:application/pdf}, } @article{narin_bibliometric_1996, title = {Bibliometric performance measures}, volume = {36}, copyright = {http://www.springer.com/tdm}, issn = {0138-9130, 1588-2861}, url = {http://link.springer.com/10.1007/BF02129596}, doi = {10.1007/BF02129596}, language = {en}, number = {3}, urldate = {2024-08-14}, journal = {Scientometrics}, author = {Narin, F. and Hamilton, Kimberly S.}, month = jul, year = {1996}, keywords = {SCIENCE, TECHNOLOGY}, pages = {293--310}, annote = {Times Cited in Web of Science Core Collection:  166Total Times Cited:  179Cited Reference Count:  17}, annote = {Times Cited in Web of Science Core Collection:  166Total Times Cited:  179Cited Reference Count:  17}, file = {Narin et Hamilton - 1996 - Bibliometric performance measures.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\NJBLWCMU\\Narin et Hamilton - 1996 - Bibliometric performance measures.pdf:application/pdf}, } @article{fassin_use_2023, title = {Use of {Bibliometrics}-{Related} {Terms}, their {Evolution}, and the {Growth} of {Metrics} in {Science}}, volume = {12}, issn = {23216654, 23200057}, url = {https://jscires.org/article/6489}, doi = {10.5530/jscires.12.2.048}, abstract = {This article analyses the evolution of the most-used terms referring to the (broad) field of bibliometrics. It compares the number of publications on bibliometrics, scientometrics, informetrics, web(o)metrics, altmetrics, and the science of science, in three international databases, the Web of Science, Scopus, and Dimensions. We found that the relative number of documents using one of the metrics-related terms is showing a more than exponential increase. This illustrates the increasing importance of metrics in the world of science. While most terms separately show a clear increase in use, web(o)metrics and perhaps, informetrics, seem to have reached their top. Bibliometrics and scientometrics are the most-used terms, with, nowadays, the term bibliometrics being used about five times more than the term scientometrics. Any comprehensive bibliometric study should make use of a combination of related keywords to cover the whole field of study.}, language = {en}, number = {2}, urldate = {2024-08-14}, journal = {Journal of Scientometric Research}, author = {Fassin, Yves and Rousseau, Ronald}, month = aug, year = {2023}, keywords = {Bibliometrics, Altmetrics, Database queries, Informetrics, Quantitative science studies, Science of science, Scientometrics, Webmetrics}, pages = {509--519}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  22}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  22}, file = {Fassin et Rousseau - 2023 - Use of Bibliometrics-Related Terms, their Evolutio.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\TENAJGIU\\Fassin et Rousseau - 2023 - Use of Bibliometrics-Related Terms, their Evolutio.pdf:application/pdf}, } @article{xu_multi-source_2017, title = {Multi-source data fusion study in scientometrics}, volume = {111}, issn = {0138-9130}, doi = {10.1007/s11192-017-2290-5}, abstract = {This paper provides an introduction to multi-source data fusion (MSDF) and comprehensively overviews the ingredients and challenges of MSDF in scientometrics. As compared to the MSDF methods in the sensor and other fields, and considering the features of scientometrics, in this paper an application model and procedure of MSDF in scientometrics are proposed. The model and procedure can be divided into three parts: data type integration, fusion of data relations, and ensemble clustering. Furthermore, the fusion of data relations can be divided into cross-integration of multi-mode data and matrix fusion of multi-relational data. To obtain a clearer and deeper analysis of the MSDF model, this paper further focuses on the application of MSDF in topic identification based on text analysis of scientific literatures. This paper also discusses the application of MSDF for the exploration of scientific literatures. Finally, the most suitable MSDF methods for different situations are discussed.}, language = {English}, number = {2}, journal = {SCIENTOMETRICS}, author = {Xu, HY and Yue, ZH and Wang, C and Dong, K and Pang, HS and Han, ZB}, month = may, year = {2017}, keywords = {Scientometrics, SCIENCE, Data fusion, MAPS, MODEL, Multi-mode analysis, Multi-source data, Relations fusion, VISUALIZATION, WORD ANALYSIS}, pages = {773--792}, annote = {Times Cited in Web of Science Core Collection:  13Total Times Cited:  15Cited Reference Count:  71}, annote = {Times Cited in Web of Science Core Collection:  13Total Times Cited:  15Cited Reference Count:  71}, annote = {Times Cited in Web of Science Core Collection:  13Total Times Cited:  15Cited Reference Count:  71}, } @article{kim_how_2016, title = {How are they different? {A} quantitative domain comparison of information visualization and data visualization (2000-2014)}, volume = {107}, issn = {0138-9130}, doi = {10.1007/s11192-015-1830-0}, abstract = {Information visualization and data visualization are often viewed as similar, but distinct domains, and they have drawn an increasingly broad range of interest from diverse sectors of academia and industry. This study systematically analyzes and compares the intellectual landscapes of the two domains between 2000 and 2014. The present study is based on bibliographic records retrieved from the Web of Science. Using a topic search and a citation expansion, we collected two sets of data in each domain. Then, we identified emerging trends and recent developments in information visualization and data visualization, captivated in intellectual landscapes, landmark articles, bursting keywords, and citation trends of the domains. We found out that both domains have computer engineering and applications as their shared grounds. Our study reveals that information visualization and data visualization have scrutinized algorithmic concepts underlying the domains in their early years. Successive literature citing the datasets focuses on applying information and data visualization techniques to biomedical research. Recent thematic trends in the fields reflect that they are also diverging from each other. In data visualization, emerging topics and new developments cover dimensionality reduction and applications of visual techniques to genomics. Information visualization research is scrutinizing cognitive and theoretical aspects. In conclusion, information visualization and data visualization have co-evolved. At the same time, both fields are distinctively developing with their own scientific interests.}, language = {English}, number = {1}, journal = {SCIENTOMETRICS}, author = {Kim, MC and Zhu, YJ and Chen, CM}, month = apr, year = {2016}, keywords = {Scientometrics, BIOTIN SYNTHASE, CLUSTER BINDING-SITES, Data science, Data visualization, DIMENSIONALITY REDUCTION, Domain analysis, EMERGING TRENDS, ESCHERICHIA-COLI, Information visualization, IRON-SULFUR CLUSTER, OF-THE-ART, PYRUVATE FORMATE-LYASE, RADICAL SAM, S-ADENOSYLMETHIONINE, Visual analytics}, pages = {123--165}, annote = {Times Cited in Web of Science Core Collection:  38Total Times Cited:  46Cited Reference Count:  158}, annote = {Times Cited in Web of Science Core Collection:  38Total Times Cited:  46Cited Reference Count:  158}, annote = {Times Cited in Web of Science Core Collection:  38Total Times Cited:  46Cited Reference Count:  158}, } @article{santos_symmetry_2023, title = {Symmetry in {Scientific} {Collaboration} {Networks}: {A} {Study} {Using} {Temporal} {Graph} {Data} {Science} and {Scientometrics}}, volume = {15}, issn = {2073-8994}, doi = {10.3390/sym15030601}, abstract = {This article proposes a novel approach that leverages graph theory, machine learning, and graph embedding to evaluate research groups comprehensively. Assessing the performanceand impact of research groups is crucial for funding agencies and research institutions, but many traditional methods often fail to capture the complex relationships between the evaluated elements.In this sense, our methodology transforms publication data into graph structures, allowing the visualization and quantification of relationships between researchers, publications, and institutions.By incorporating symmetry properties, we offer a more in-depth evaluation of research groups cohesiveness and structure over time. This temporal evaluation methodology bridges the gap between unstructured scientometrics networks and the evaluation process, making it a valuable tool for decision-making procedures. A case study is defined to demonstrate the potential to providevaluable insights into the dynamics and limitations of research groups, which ultimately reinforces the feasibility of the proposed approach when supporting decision making for funding agencies andresearch institutions.}, language = {English}, number = {3}, journal = {SYMMETRY-BASEL}, author = {Santos, BS and Silva, I and Costa, DG}, month = mar, year = {2023}, keywords = {scientometrics, graph data science, graph embedding, machine learning, symmetry properties, temporal analysis}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  38}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  38}, annote = {Times Cited in Web of Science Core Collection:  1Total Times Cited:  1Cited Reference Count:  38}, } @article{hou_spatial-temporal_2018, title = {The spatial-temporal transfer of scientometrics research topics based on citation analysis}, volume = {23}, issn = {1394-6234}, doi = {10.22452/mjlis.vol23no3.4}, abstract = {In this study, the spatial-temporal transfer of research topics in the field of scientometrics was analysed through citation analysis and information visualization tools such as CiteSpace and Google Fusion Tables software. We collected 12,839 articles, including 214,748 references, about citation analysis in Science Citation Index-Expanded (SCI-E) and Social Science Citation Index (SSCI) databases for the period of 1971 to July 2016 as the data source. We obtained the following findings: The transfer of central research topics in the field of scientometrics is accelerating. There have been three milestones: the middle of the 1990s, 2005, and 2010. The number of central research topics has also changed from one between 1971 and 1993 to two after 1994 and three after 2008. At the same time, the geographical centres of scientometrics research showed a general shift from the US and Britain to Italy, the Netherlands, Belgium, Spain, and China. At present, the countries that are centres of research include the Netherlands, US, Belgium, China, Spain, and Italy. There is a close positive correlation between the transfer of the central research topic and the transformation of the country to a centre of research. The countries acting as centres of research enjoy not only a high output of literature, but also a great academic influence. Both the theoretical and practical implications of the results are discussed.}, language = {English}, number = {3}, journal = {MALAYSIAN JOURNAL OF LIBRARY \& INFORMATION SCIENCE}, author = {Hou, JH and Yang, XC}, year = {2018}, keywords = {IMPACT, Scientometrics, INDEX, Information visualization, COCITATION, COLLABORATION NETWORKS, PERSPECTIVE, Scientific impact, Societal impact, Transfer of research centres, TRIPLE-HELIX}, pages = {49--68}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  48}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  48}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  48}, } @article{kraker_visualization_2015, title = {Visualization of co-readership patterns from an online reference management system}, volume = {9}, issn = {1751-1577}, doi = {10.1016/j.joi.2014.12.003}, abstract = {In this paper, we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating knowledge domain visualizations. First, we investigate the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69\% of the publications in an average user library can be attributed to a single subject area. Then, we use co-readership patterns to map the field of educational technology. The resulting visualization prototype, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80\% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent. (C) 2015 Elsevier Ltd. All rights reserved.}, language = {English}, number = {1}, journal = {JOURNAL OF INFORMETRICS}, author = {Kraker, P and Schlögl, C and Jack, K and Lindstaedt, S}, month = jan, year = {2015}, keywords = {Altmetrics, IMPACT, METRICS, SCIENCE, CITATION, COCITATION ANALYSIS, Knowledge domain visualization, Mapping, Readership statistics, Relational scientometrics, Topical distribution}, pages = {169--182}, annote = {Times Cited in Web of Science Core Collection:  10Total Times Cited:  11Cited Reference Count:  55}, annote = {Times Cited in Web of Science Core Collection:  10Total Times Cited:  11Cited Reference Count:  55}, annote = {Times Cited in Web of Science Core Collection:  10Total Times Cited:  11Cited Reference Count:  55}, } @article{bornmann_detection_2011, title = {The detection of "hot regions" in the geography of science-{A} visualization approach by using density maps}, volume = {5}, issn = {1751-1577}, doi = {10.1016/j.joi.2011.04.006}, abstract = {Spatial scientometrics has attracted a lot of attention in the very recent past. The visualization methods (density maps) presented in this paper allow for an analysis revealing regions of excellence around the world using computer programs that are freely available. Based on Scopus and Web of Science data, field-specific and field-overlapping scientific excellence can be identified in broader regions (worldwide or for a specific continent) where high quality papers (highly cited papers or papers published in Nature or Science) were published. We used a geographic information system to produce our density maps. We also briefly discuss the use of Google Earth. (C) 2011 Elsevier Ltd. All rights reserved.}, language = {English}, number = {4}, journal = {JOURNAL OF INFORMETRICS}, author = {Bornmann, L and Waltman, L}, month = oct, year = {2011}, keywords = {BIBLIOMETRIC INDICATORS, CITIES, Density map, Geographic information system, Geographical mapping, Highly cited paper, NETWORKS, Spatial scientometrics}, pages = {547--553}, annote = {Times Cited in Web of Science Core Collection:  50Total Times Cited:  53Cited Reference Count:  18}, annote = {Times Cited in Web of Science Core Collection:  50Total Times Cited:  53Cited Reference Count:  18}, annote = {Times Cited in Web of Science Core Collection:  50Total Times Cited:  53Cited Reference Count:  18}, } @article{riyanto_development_2019, title = {Development of collaboration matrix using co-occurrence and combinatoric system as scientometrics analysis}, volume = {13}, issn = {0973-7766}, doi = {10.1080/09737766.2020.1723450}, abstract = {Purpose - The purpose of this study is to propose a new method for revealing the collaboration frequencies among the author's name and the author's affiliation through various analysis and visualization methods. Design/methodology/approach - This study takes metadata of the author's name, author's affiliate, and keyword from National Scientific Repository (RIN). Each article will be extracted accord to the entity, the author's name is separated into first author, second author, third author, etc. The affiliation is also separated according to the author's affiliation using machine learning algorithms. Findings - The implementation of the collaboration matrix form of visualization can be used effectively in looking at the number of collaborative frequencies of scientific works among author's names and author's affiliations. Presentations and calculations of keywords that often appear in each scientific paper resulting from collaboration between name pairs can be used to identify the contents of the study of scientific articles as a whole, see the topics discussed and find out the trends and interests of research. Originality/value - This study applied collaboration matrix using cooccurrence and combinatoric methods. The result of the analysis is the number of collaboration among the authors and the highest number of collaborations will be placed on the top rank.}, language = {English}, number = {2}, journal = {COLLNET JOURNAL OF SCIENTOMETRICS AND INFORMATION MANAGEMENT}, author = {Riyanto, S and Subagyo, H and Marlina, E and Yaniasih, Y and Rodiah, R}, month = jul, year = {2019}, keywords = {Scientometrics, Co-author network, Co-author pattern, Co-occurrence, Collaboration matrix, Combinatoric system, NETWORK, PATTERNS}, pages = {247--267}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  21}, } @article{larowe_scholarly_2009, title = {The {Scholarly} {Database} and its utility for scientometrics research}, volume = {79}, issn = {0138-9130}, doi = {10.1007/s11192-009-0414-2}, abstract = {The Scholarly Database aims to serve researchers and practitioners interested in the analysis, modelling, and visualization of large-scale data sets. A specific focus of this database is to support macro-evolutionary studies of science and to communicate findings via knowledge-domain visualizations. Currently, the database provides access to about 18 million publications, patents, and grants. About 90\% of the publications are available in full text. Except for some datasets with restricted access conditions, the data can be retrieved in raw or pre-processed formats using either a web-based or a relational database client. This paper motivates the need for the database from the perspective of bibliometric/scientometric research. It explains the database design, setup, etc., and reports the temporal, geographical, and topic coverage of data sets currently served via the database. Planned work and the potential for this database to become a global testbed for information science research are discussed at the end of the paper.}, language = {English}, number = {2}, journal = {SCIENTOMETRICS}, author = {LaRowe, G and Ambre, S and Burgoon, J and Ke, W and Börner, K}, month = may, year = {2009}, keywords = {SCIENCE, KNOWLEDGE DOMAINS}, pages = {219--234}, annote = {Times Cited in Web of Science Core Collection:  19Total Times Cited:  21Cited Reference Count:  13}, annote = {Times Cited in Web of Science Core Collection:  19Total Times Cited:  21Cited Reference Count:  13}, annote = {Times Cited in Web of Science Core Collection:  19Total Times Cited:  21Cited Reference Count:  13}, } @article{sinha_altmetrics_2020, title = {Altmetrics {Research} {Progress}: {A} {Bibliometric} {Analysis} and {Visualization}}, volume = {9}, issn = {2321-6654}, doi = {10.5530/jscires.9.3.37}, abstract = {The present study explores the altmetrics research area through bibliometric analysis and visualization. For the investigation of research material Scopus database was chosen, to obtain the bibliographic data. The search in database resulted in 973 documents. The data was obtained in CSV file format and for the basic data processing excel was used whereas for the visualization network VOSviewer software was employed. The investigation revealed that around 30.34\% documents have open access. The major document type was articles (65.05\%), with journals (81.39\%) as major sources for document and English (92.70\%) as the dominant language for documents. The research also revealed that there has been a constant rise in the number of publications in the field since its inception and documents belong to different subject areas with social science leading the way. The major sources were Scientometrics (12.33\%) and Journal of Informetrics (3.18\%). Most productive authors were Mike Thelwall (41 documents), Lutz Bornmann (32 documents): most producing countries were USA (264 documents) United Kingdom (141 documents); and most producing organizations were University of Wolverhampton with 43 documents, Administrative Headquarters of the Max Planck Society with 32 documents. The visualization of author network revealed that collaborations between top authors are taking place but in a close knitted environment where one group of authors do not collaborate much with other group. The country collaboration network revealed that the top countries are extensively collaborating without any restrictions and developing countries like India, Pakistan are part of this collaboration network as well. The term map created out of the abstract and title information of research documents also revealed the trend of research in the altmetrics field.}, language = {English}, number = {3}, journal = {JOURNAL OF SCIENTOMETRIC RESEARCH}, author = {Sinha, PK and Sahoo, SB and Gajbe, SB and Chakrabory, K and Mahato, SS}, month = sep, year = {2020}, keywords = {Altmetrics, ARTICLES, Bibliometric Analysis, COLLABORATION, PUBLICATIONS, RESEARCH IMPACT, Research Progress, SCIENTOMETRICS, Scopus, VOSviewer}, pages = {300--309}, annote = {Times Cited in Web of Science Core Collection:  5Total Times Cited:  5Cited Reference Count:  48}, annote = {Times Cited in Web of Science Core Collection:  5Total Times Cited:  5Cited Reference Count:  48}, annote = {Times Cited in Web of Science Core Collection:  5Total Times Cited:  5Cited Reference Count:  48}, } @article{light_open_2014, title = {Open data and open code for big science of science studies}, volume = {101}, issn = {0138-9130}, doi = {10.1007/s11192-014-1238-2}, abstract = {Historically, science of science (Sci2) studies have been performed by single investigators or small teams. As the size and complexity of data sets and analyses scales up, a "Big Science'' approach (Price, Little science, big science, 1963) is required that exploits the expertise and resources of interdisciplinary teams spanning academic, government, and industry boundaries. Big Sci2 studies utilize "big data'', i.e., large, complex, diverse, longitudinal, and/or distributed datasets that might be owned by different stake-holders. They apply a systems science approach to uncover hidden patterns, bursts of activity, correlations, and laws. They make available open data and open code in support of replication of results, iterative refinement of approaches and tools, and education. This paper introduces a database-tool infrastructure that was designed to support big Sci2 studies. The open access Scholarly Database (http://sdb.cns.iu.edu) provides easy access to 26 million paper, patent, grant, and clinical trial records. The open source Sci2 tool (http://sci2.cns.iu.edu) supports temporal, geospatial, topical, and network studies. The scalability of the infrastructure is examined. Results show that temporal analyses scale linearly with the number of records and file size, while the geospatial algorithm showed quadratic growth. The number of edges rather than nodes determined performance for network based algorithms.}, language = {English}, number = {2}, journal = {SCIENTOMETRICS}, author = {Light, RP and Polley, DE and Börner, K}, month = nov, year = {2014}, keywords = {Big data, Open data, Scalability, Visualization software, Workflows}, pages = {1535--1551}, annote = {Times Cited in Web of Science Core Collection:  40Total Times Cited:  41Cited Reference Count:  14}, annote = {Times Cited in Web of Science Core Collection:  40Total Times Cited:  41Cited Reference Count:  14}, annote = {Times Cited in Web of Science Core Collection:  40Total Times Cited:  41Cited Reference Count:  14}, } @article{gu_mapping_2021, title = {Mapping the {Research} on {Knowledge} {Transfer}: {A} {Scientometrics} {Approach}}, volume = {9}, issn = {2169-3536}, doi = {10.1109/ACCESS.2021.3061576}, abstract = {The research on knowledge transfer (KT) has attracted much attention from the researcher and academicians from the last decade. Bibliometric and visualization research on this topic is insufficient. This study aims to analyze the leading trends in the literature of KT and provide a holistic view. Data for this analysis is extracted from the Scopus database. VOSviewer software is used to map different bibliometric indicators such as bibliographic coupling and co-occurrence. This study identifies the most productive countries, authors, journals, and the most prolific publications in knowledge transfer research during 2010-2019. Moreover, it also identifies the most popular themes and suggests some future directions. The study also provides an overview of the trends and trajectories of KT with a visual and schematic frame, which may help the researchers and the practitioners understand the current trends and future research directions.}, language = {English}, journal = {IEEE ACCESS}, author = {Gu, ZY and Meng, FC and Farrukh, M}, year = {2021}, keywords = {bibliometric analysis, Bibliometrics, Collaboration, Couplings, Databases, Knowledge transfer, Market research, publication metrics, Software}, pages = {34647--34659}, annote = {Times Cited in Web of Science Core Collection:  39Total Times Cited:  39Cited Reference Count:  50}, annote = {Times Cited in Web of Science Core Collection:  39Total Times Cited:  39Cited Reference Count:  50}, annote = {Times Cited in Web of Science Core Collection:  39Total Times Cited:  39Cited Reference Count:  50}, } @article{di_caro_d-index_2012, title = {The d-index: {Discovering} dependences among scientific collaborators from their bibliographic data records}, volume = {93}, issn = {0138-9130}, doi = {10.1007/s11192-012-0762-1}, abstract = {The evaluation of the work of a researcher and its impact on the research community has been deeply studied in literature through the definition of several measures, first among all the h-index and its variations. Although these measures represent valuable tools for analyzing researchers' outputs, they usually assume the co-authorship to be a proportional collaboration between the parts, missing out their relationships and the relative scientific influences. In this work, we propose the d-index, a novel measure that estimates the dependence degree between authors on their research environment along their entire scientific publication history. We also present a web application that implements these ideas and provides a number of visualization tools for analyzing and comparing scientific dependences among all the scientists in the DBLP bibliographic database. Finally, relying on this web environment, we present case and user studies that highlight both the validity and the reliability of the proposed evaluation measure.}, language = {English}, number = {3}, journal = {SCIENTOMETRICS}, author = {Di Caro, L and Cataldi, M and Schifanella, C}, month = dec, year = {2012}, keywords = {H-INDEX, Research evaluation, Data visualization, Collaboration analysis, Evaluation metrics, SOCIAL NETWORK, Social networks}, pages = {583--607}, annote = {Times Cited in Web of Science Core Collection:  8Total Times Cited:  8Cited Reference Count:  34}, annote = {Times Cited in Web of Science Core Collection:  8Total Times Cited:  8Cited Reference Count:  34}, annote = {Times Cited in Web of Science Core Collection:  8Total Times Cited:  8Cited Reference Count:  34}, } @article{mohabbati-kalejahi_streamlining_2017, title = {Streamlining science with structured data archives: insights from stroke rehabilitation}, volume = {113}, issn = {0138-9130}, doi = {10.1007/s11192-017-2482-z}, abstract = {Recent advances in bibliometrics have focused on text-mining to organize scientific disciplines based on author networks, keywords, and citations. These approaches provide insights, but fail to capture important experimental data that exist in many scientific disciplines. The objective of our paper is to show how such data can be used to organize the literature within a discipline, and identify knowledge gaps. Our approach is especially important for disciplines relying on randomized control trials. Using stroke rehabilitation as an informative example, we construct an interactive graphing platform to address domain general scientific questions relating to bias, common data elements, and relationships between key constructs in a field. Our platform allows researchers to ask their own questions and systematically search the literature from the data up.}, language = {English}, number = {2}, journal = {SCIENTOMETRICS}, author = {Mohabbati-Kalejahi, N and Yazdi, MAA and Megahed, FM and Schaefer, SY and Boyd, LA and Lang, CE and Lohse, KR}, month = nov, year = {2017}, keywords = {Bibliometrics, Data visualization, CLINICAL-TRIAL, DOSE-RESPONSE, Meta-science, METAANALYSIS, MOTOR RECOVERY, Randomized controlled trials}, pages = {969--983}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  44}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  44}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  44}, } @article{dunaiski_exploratory_2017, title = {Exploratory search of academic publication and citation data using interactive tag cloud visualizations}, volume = {110}, issn = {0138-9130}, doi = {10.1007/s11192-016-2236-3}, abstract = {Acquiring an overview of an unfamiliar discipline and exploring relevant papers and journals is often a laborious task for researchers. In this paper we show how exploratory search can be supported on a large collection of academic papers to allow users to answer complex scientometric questions which traditional retrieval approaches do not support optimally. We use our ConceptCloud browser, which makes use of a combination of concept lattices and tag clouds, to visually present academic publication data (specifically, the ACM Digital Library) in a browsable format that facilitates exploratory search. We augment this dataset with semantic categories, obtained through automatic keyphrase extraction from papers' titles and abstracts, in order to provide the user with uniform keyphrases of the underlying data collection. We use the citations and references of papers to provide additional mechanisms for exploring relevant research by presenting aggregated reference and citation data not only for a single paper but also across topics, authors and journals, which is novel in our approach. We conduct a user study to evaluate our approach in which we asked 34 participants, from different academic backgrounds with varying degrees of research experience, to answer a variety of scientometric questions using our ConceptCloud browser. Participants were able to answer complex scientometric questions using our ConceptCloud browser with a mean correctness of 73\%, with the user's prior research experience having no statistically significant effect on the results.}, language = {English}, number = {3}, journal = {SCIENTOMETRICS}, author = {Dunaiski, M and Greene, GJ and Fischer, B}, month = mar, year = {2017}, keywords = {PAPER, NETWORKS, Automatic keyphrase extraction, Citation analysis, COLLECTIONS, Exploratory search, Formal concept analysis, SIMILARITY, Tag clouds, User study}, pages = {1539--1571}, annote = {Times Cited in Web of Science Core Collection:  9Total Times Cited:  11Cited Reference Count:  57}, annote = {Times Cited in Web of Science Core Collection:  9Total Times Cited:  11Cited Reference Count:  57}, annote = {Times Cited in Web of Science Core Collection:  9Total Times Cited:  11Cited Reference Count:  57}, } @article{lee_viziometrics_2018, title = {Viziometrics: {Analyzing} {Visual} {Information} in the {Scientific} {Literature}}, volume = {4}, issn = {2332-7790}, doi = {10.1109/TBDATA.2017.2689038}, abstract = {Scientific results are communicated visually in the literature through diagrams, visualizations, and photographs. These information-dense objects have been largely ignored in bibliometrics and scientometrics studies when compared to citations and text. In this paper, we use techniques from computer vision and machine learning to classify more than 8 million figures from PubMed into five figure types and study the resulting patterns of visual information as they relate to scholarly impact. We find that the distribution of figures and figure types in the literature has remained relatively constant over time, but can vary widely across field and topic. Remarkably, we find a significant correlation between scientific impact and the use of visual information, where higher impact papers tend to include more diagrams, and to a lesser extent more plots. To explore these results and other ways of extracting this visual information, we have built a visual browser to illustrate the concept and explore design alternatives for supporting viziometric analysis and organizing visual information. We use these results to articulate a new research agenda-viziometrics-to study the organization and presentation of visual information in the scientific literature.}, language = {English}, number = {1}, journal = {IEEE TRANSACTIONS ON BIG DATA}, author = {Lee, PS and West, JD and Howe, B}, month = jan, year = {2018}, keywords = {bibliometrics, IMPACT, information retrieval, scientometrics, BRAIN, figure retrieval, GRAPHS, JOURNALS, meta research, scholarly communication, TABLES, TEXT, Viziometrics}, pages = {117--129}, annote = {Times Cited in Web of Science Core Collection:  35Total Times Cited:  40Cited Reference Count:  40}, annote = {Times Cited in Web of Science Core Collection:  35Total Times Cited:  40Cited Reference Count:  40}, annote = {Times Cited in Web of Science Core Collection:  35Total Times Cited:  40Cited Reference Count:  40}, } @article{baas_scopus_2020, title = {Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies}, volume = {1}, issn = {2641-3337}, doi = {10.1162/qss_a_00019}, abstract = {Scopus is among the largest curated abstract and citation databases, with a wide global and regional coverage of scientific journals, conference proceedings, and books, while ensuring only the highest quality data are indexed through rigorous content selection and re-evaluation by an independent Content Selection and Advisory Board. Additionally, extensive quality assurance processes continuously monitor and improve all data elements in Scopus. Besides enriched metadata records of scientific articles, Scopus offers comprehensive author and institution profiles, obtained from advanced profiling algorithms and manual curation, ensuring high precision and recall. The trustworthiness of Scopus has led to its use as bibliometric data source for large-scale analyses in research assessments, research landscape studies, science policy evaluations, and university rankings. Scopus data have been offered for free for selected studies by the academic research community, such as through application programming interfaces, which have led to many publications employing Scopus data to investigate topics such as researcher mobility, network visualizations, and spatial bibliometrics. In June 2019, the International Center for the Study of Research was launched, with an advisory board consisting of bibliometricians, aiming to work with the scientometric research community and offering a virtual laboratory where researchers will be able to utilize Scopus data.}, language = {English}, number = {1}, journal = {QUANTITATIVE SCIENCE STUDIES}, author = {Baas, J and Schotten, M and Plume, A and Côté, G and Karimi, R}, year = {2020}, keywords = {bibliometrics, scientometrics, CITATION, PATTERNS, COLLABORATION, abstract and citation database, author profile, bibliographic database, citation linking, Content Selection and Advisory Board, CSAB, data cleaning, data clustering, data curation, data linking, GEOGRAPHY, HOT, ICSR, institution profile, International Center for the Study of Research, network visualization, ORCiD, quality assurance, research assessment, researcher mobility, science policy evaluation, university ranking}, pages = {377--386}, annote = {Times Cited in Web of Science Core Collection:  476Total Times Cited:  491Cited Reference Count:  49}, annote = {Times Cited in Web of Science Core Collection:  476Total Times Cited:  491Cited Reference Count:  49}, annote = {Times Cited in Web of Science Core Collection:  476Total Times Cited:  491Cited Reference Count:  49}, } @article{bhatia_data_2021, title = {Data congestion in {VANETs}: research directions and new trends through a bibliometric analysis}, volume = {77}, issn = {0920-8542}, doi = {10.1007/s11227-020-03520-7}, abstract = {Vehicular Ad hoc Networks (VANETs) become increasingly popular in academia and manufacturing businesses. The VANETs domain attracts massive attention from various authors all over the world on a large scale. However, substantial research efforts are expected in the VANETs field to solve the data congestion problem. For this, it is vital to state the current status of research in this domain. As the research publications have substantially increased since 2009, a bibliometric analysis is necessary for researchers to understand actual results and findings in this area. This paper examines and analyzes the status of research trends between 2010 and 2019 for the domain "Data congestion in VANETs" by applying various parameters. As extracted from the Scopus database till December 31, 2019, a total of 11,109 publications are associated with the VANETs domain. Moreover, 434 publications among the collection are related to data congestion in the VANETs field. Finally, a software tool named the VOSviewer is used to create and envision the selected field's bibliometric networks. This analysis paper will help the researchers to catch the research trends of data congestion in VANETs.}, language = {English}, number = {7}, journal = {JOURNAL OF SUPERCOMPUTING}, author = {Bhatia, TK and Ramachandran, RK and Doss, R and Pan, L}, month = jul, year = {2021}, keywords = {Bibliometric analysis, SCIENCE, CITATION, SCIENTOMETRICS, Visualization, AD HOC NETWORKS, Data Congestion, DATA DISSEMINATION, MAPPING SOFTWARE, POWER-CONTROL, ROUTING PROTOCOL, SCHEME, SECURITY CHALLENGES, Vehicular Ad hoc Networks, VOSviewer Tool}, pages = {6586--6628}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  111}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  111}, annote = {Times Cited in Web of Science Core Collection:  2Total Times Cited:  2Cited Reference Count:  111}, } @article{glanzel_various_2022, title = {Various aspects of interdisciplinarity in research and how to quantify and measure those}, volume = {127}, issn = {0138-9130}, doi = {10.1007/s11192-021-04133-4}, abstract = {Interdisciplinary research figures high on today's policy agendas. This short introduction and overview sketches the complexity of defining and mapping the nature of interdisciplinary research (IDR). The paper focuses on the different approaches to IDR and different methods applied in bibliometric studies that allow measuring it. These methods should not only be able to capture quantitative aspects of IDR but also to monitor evolutionary aspects and help answer the question of whether IDR stimulates collaboration and results in larger impact and visibility. Two specific indicators, variety and disparity, are developed, validated and applied to bibliometric data. They enable the visualization of the interdisciplinary nature of research activities at various levels of analysis (both institutional and individual). And, given the longitudinal character of bibliometric data and databases, both indicators allow for mapping time-dependent phenomena and evolutions. Relevant examples based on the literature and recent results from research conducted at the Leuven bibliometrics group of ECOOM (e.g., Glanzel et al., Proceedings of the 18(th) International Conference of the International Society of Scientometrics and Informetrics, 453-464, 2021; Huang et al., Proceedings of the 18(th) International Conference of the International Society of Scientometrics and Informetrics, 533-538, 2021) are given, and concrete proposals for future research are articulated.}, language = {English}, number = {9}, journal = {SCIENTOMETRICS}, author = {Glänzel, W and Debackere, K}, month = sep, year = {2022}, keywords = {IMPACT, INDICATORS, SCIENCE, Citation impact, CLASSIFICATION, DIVERSITY, FIELDS, Interdisciplinary research, Knowledge integration, Scientific collaboration}, pages = {5551--5569}, annote = {Times Cited in Web of Science Core Collection:  16Total Times Cited:  17Cited Reference Count:  56}, annote = {Times Cited in Web of Science Core Collection:  16Total Times Cited:  17Cited Reference Count:  56}, annote = {Times Cited in Web of Science Core Collection:  16Total Times Cited:  17Cited Reference Count:  56}, } @article{harries_hyperlinks_2004, title = {Hyperlinks as a data source for science mapping}, volume = {30}, issn = {0165-5515}, doi = {10.1177/0165551504046736}, abstract = {Hyperlinks between academic web sites, like citations, can potentially be used to map disciplinary structures and identify evidence of connections between disciplines. In this paper we classified a sample of links originating in three different disciplines: maths, physics and sociology. Links within a discipline were found to be different in character to links between pages in different disciplines. There were also disciplinary differences in both types of link. As a consequence, we argue that interpretations of web science maps covering multiple disciplines will need to be sensitive to the contexts of the links mapped.}, language = {English}, number = {5}, journal = {JOURNAL OF INFORMATION SCIENCE}, author = {Harries, G and Wilkinson, D and Price, L and Fairclough, R and Thelwall, M}, year = {2004}, keywords = {COMMUNICATION, IMPACT, webometrics, scientometrics, CITATION, PATTERNS, COLLABORATION, COAUTHORSHIP, content analysis, domain visualization, hyperlinks, interdisciplinary relationships, intradisciplinary relationships, university web sites, web pages}, pages = {436--447}, annote = {Times Cited in Web of Science Core Collection:  32Total Times Cited:  34Cited Reference Count:  45}, annote = {Times Cited in Web of Science Core Collection:  32Total Times Cited:  34Cited Reference Count:  45}, annote = {Times Cited in Web of Science Core Collection:  32Total Times Cited:  34Cited Reference Count:  45}, } @article{hashem_mapreduce_2016, title = {{MapReduce}: {Review} and open challenges}, volume = {109}, issn = {0138-9130}, doi = {10.1007/s11192-016-1945-y}, abstract = {The continuous increase in computational capacity over the past years has produced an overwhelming flow of data or big data, which exceeds the capabilities of conventional processing tools. Big data signify a new era in data exploration and utilization. The MapReduce computational paradigm is a major enabler for underlying numerous big data platforms. MapReduce is a popular tool for the distributed and scalable processing of big data. It is increasingly being used in different applications primarily because of its important features, including scalability, fault tolerance, ease of programming, and flexibility. Thus, bibliometric analysis and review was conducted to evaluate the trend of MapReduce research assessment publications indexed in Scopus from 2006 to 2015. This trend includes the use of the MapReduce framework for big data processing and its development. The study analyzed the distribution of published articles, countries, authors, keywords, and authorship pattern. For data visualization, VOSviewer program was used to produce distance- and graph-based maps. The top 10 most cited articles were also identified based on the citation count of publications. The study utilized productivity measures, domain visualization techniques and co-word to explore papers related to MapReduce in the field of big data. Moreover, the study discussed the most influential articles contributed to the improvements in MapReduce and reviewed the corresponding solutions. Finally, it presented several open challenges on big data processing with MapReduce as future research directions.}, language = {English}, number = {1}, journal = {SCIENTOMETRICS}, author = {Hashem, IAT and Anuar, NB and Gani, A and Yaqoob, I and Xia, F and Khan, SU}, month = oct, year = {2016}, keywords = {SCIENCE, PERFORMANCE, SCOPUS, WEB, Big data, Bibliometric, BIBLIOMETRIC ANALYSIS, BIG-DATA, CLOUDS, FRAMEWORK, Hadoop, MapReduce}, pages = {389--422}, annote = {Times Cited in Web of Science Core Collection:  46Total Times Cited:  49Cited Reference Count:  90}, annote = {Times Cited in Web of Science Core Collection:  46Total Times Cited:  49Cited Reference Count:  90}, annote = {Times Cited in Web of Science Core Collection:  46Total Times Cited:  49Cited Reference Count:  90}, } @article{khasseh_intellectual_2017, title = {Intellectual structure of knowledge in {iMetrics}: {A} co-word analysis}, volume = {53}, issn = {0306-4573}, doi = {10.1016/j.ipm.2017.02.001}, abstract = {As an iMetrics technique, co-word analysis is used to describe the status of various subject areas, however, iMetrics itself is not examined by a co-word analysis. For the purpose of using co-word analysis, this study tries to investigate the intellectual structure of iMetrics during the period of 1978 to 2014. The research data are retrieved from two core journals on iMetrics research (Scientometrics, and Journal of lnfonnetrics) and relevant articles in six journals publishing iMetrics studies. Application of hierarchical clustering led to the formation of 11 clusters representing the intellectual structure of iMetrics, including "Scientometric Databases and Indicators," "Citation Analysis," "Sociology of Science," "Issues Related to Rankings of Universities, Journals, etc.," "Information Visualization and Retrieval," "Mapping Intellectual Structure of Science," "Webometrics," "Industry-University Government Relations," "Technometrics (Innovation and Patents), "Scientific Collaboration in Universities", and "Basics of Network Analysis." Furthermore, a two-dimensional map and a strategic diagram are drawn to clarify the structure, maturity, and cohesion of clusters. (c) 2017 Elsevier Ltd. All rights reserved.}, language = {English}, number = {3}, journal = {INFORMATION PROCESSING \& MANAGEMENT}, author = {Khasseh, AA and Soheili, F and Moghaddam, HS and Chelak, AM}, month = may, year = {2017}, keywords = {LIBRARY, INFORMATION-SCIENCE, NETWORKS, SCIENTOMETRICS, BIBLIOMETRIC ANALYSIS, Co-word analysis, DISSERTATIONS, EVOLUTION, FIELD, iMetrics, Information metrics, INFORMETRICS, Knowledge structure, RESEARCH TRENDS, Strategic diagram}, pages = {705--720}, annote = {Times Cited in Web of Science Core Collection:  116Total Times Cited:  124Cited Reference Count:  70}, annote = {Times Cited in Web of Science Core Collection:  116Total Times Cited:  124Cited Reference Count:  70}, annote = {Times Cited in Web of Science Core Collection:  116Total Times Cited:  124Cited Reference Count:  70}, } @article{markscheffel_comparison_2021, title = {Comparison of two science mapping tools based on software technical evaluation and bibliometric case studies}, volume = {15}, issn = {0973-7766}, doi = {10.1080/09737766.2021.1960220}, abstract = {Bibliometrics is used to apply statistical methods to books articles, and other publication. One research topic of bibliometrics is science mapping, which examines scientific objects to determine the cognitive structure, development, and acting persons. With CiteSpace and VOSviewer two of the most popular visualization tools are compared. The evaluation of the software solutions is carried out in two steps, the first step is a purely software technical evaluation based on the framework of Jadhav and Sonar (2011). In addition to functional similarities and differences between the tools, qualitative and technical aspects are examined. Both CiteSpace and VOSviewer, share a large number of bibliometric functionalities, which are each extended by additional functions. They use different algorithms for normalization, mapping and clustering. In the second part, on the basis of own case studies, in which selected bibliometric analyses (Co-Occurrence-, Co-Citation- and Co-Authorshipanalyses) are carried out, the workflow of solving a given task with these tools is analyzed and the results are evaluated. Both tools support the steps of a science mapping process, which consists of the phases of data retrieval, preprocessing, network extraction, normalization, mapping, analysis, visualization and interpretation. As a result, can be noted that visualizations created with VOSviewer have better clarity and user-friendliness. CiteSpace, on the other hand, offers advantages in the evaluative analysis of network visualizations, e.g. by enabling analysis of the cluster nodes using a Cluster Explorer. or paste your abstract here as prescribed by the journal's instructions for authors. Type or paste your abstract here as prescribed by the journal's instructions for authors. Type or paste your abstract here as prescribed by the journal's instructions for authors. Type or paste your abstract here.}, language = {English}, number = {2}, journal = {COLLNET JOURNAL OF SCIENTOMETRICS AND INFORMATION MANAGEMENT}, author = {Markscheffel, B and Schröter, F}, month = jul, year = {2021}, keywords = {CiteSpace, PERSPECTIVE, VOSviewer, Science mapping, Visualization, Software evaluation}, pages = {365--396}, annote = {Times Cited in Web of Science Core Collection:  34Total Times Cited:  34Cited Reference Count:  52}, annote = {Times Cited in Web of Science Core Collection:  34Total Times Cited:  34Cited Reference Count:  52}, annote = {Times Cited in Web of Science Core Collection:  34Total Times Cited:  34Cited Reference Count:  52}, } @article{nazarovets_visualization_2024, title = {Visualization of rank-citation curves for fast detection of h-index anomalies in university metrics}, volume = {129}, issn = {0138-9130}, doi = {10.1007/s11192-023-04886-0}, abstract = {University rankings, despite facing criticism, continue to maintain their popularity. In the 2023 Scopus Ranking of Ukrainian Universities, certain institutions stood out due to their high h-index, despite modest publication and citation numbers. This phenomenon can be attributed to influential research topics or involvement in international collaborative research. However, these results may also be due to the authors' own efforts to increase the number of citations of their publications in order to improve their h-index. To investigate this, the publications from the top 30 universities in the ranking were analysed, revealing humpback rank-citation curves for two universities. These humpbacks indicate unusual trends in the citation data, especially considering the high percentage of self-citations and FWCI of analysed papers. While quantitative analysis has limitations, the combination of humped rank-citation curves, self-citations, FWCI, and previous research findings raises concerns about the possible causes of these anomalies in the citation data of the analysed universities. The method presented in this paper can aid ranking compilers and citation databases managers in identifying potential instances of citation data anomalies, emphasizing the importance of expert assessment for accurate conclusions.}, language = {English}, number = {1}, journal = {SCIENTOMETRICS}, author = {Nazarovets, S}, month = jan, year = {2024}, keywords = {Citations, Scopus, h-Index, INDICATOR, Self-citation, University rankings}, pages = {705--711}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  21}, annote = {Times Cited in Web of Science Core Collection:  0Total Times Cited:  0Cited Reference Count:  21}, } @article{lyu_global_2023, title = {Global scientific production, international cooperation, and knowledge evolution of public administration}, volume = {101}, issn = {0033-3298}, doi = {10.1111/padm.12853}, abstract = {Public administration is a discipline with considerable history, and is also a diverse, interdisciplinary field in social science. To analyze its evolution, discover the present research foci, and predict future development trends, this study applied scientometrics visualization technology to evaluate over 72,000 scientific articles from the 1920s to 2020s. This research referred to the SSCI and JCR databases to gather scientific data of the discipline and the journals' impact factor. Consequently, paper citations, cited journals, journal co-citations, author co-citations, authoritative papers, top countries, productive institutes, average references, and research collaboration trends were analyzed on the bases of the published literature. This study found top productive journals in the discipline, discovered productive countries and institutes, present the research foci, and predicted future development trends. Through this study, scientific production, international cooperation, and knowledge evolution mode of public administration research offers a clear knowledge map of the public administration discipline.}, language = {English}, number = {3}, journal = {PUBLIC ADMINISTRATION}, author = {Lyu, PH and Zhang, MZ and Liu, CJ and Ngai, EWT}, month = sep, year = {2023}, keywords = {SCIENCE, NETWORKS, BIBLIOMETRIC ANALYSIS, FIELD, EDUCATION, MANAGEMENT}, pages = {1134--1162}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  39}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  39}, annote = {Times Cited in Web of Science Core Collection:  3Total Times Cited:  3Cited Reference Count:  39}, } @article{greener_evaluating_2022, title = {Evaluating literature with bibliometrics}, volume = {30}, issn = {1049-4820, 1744-5191}, url = {https://www.tandfonline.com/doi/full/10.1080/10494820.2022.2118463}, doi = {10.1080/10494820.2022.2118463}, language = {en}, number = {7}, urldate = {2024-08-14}, journal = {Interactive Learning Environments}, author = {Greener, Sue}, month = aug, year = {2022}, pages = {1168--1169}, file = {Greener - 2022 - Evaluating literature with bibliometrics.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\LIHBJCAJ\\Greener - 2022 - Evaluating literature with bibliometrics.pdf:application/pdf}, } @article{cox_competencies_2019, title = {Competencies for bibliometrics}, volume = {51}, issn = {0961-0006, 1741-6477}, url = {http://journals.sagepub.com/doi/10.1177/0961000617728111}, doi = {10.1177/0961000617728111}, abstract = {Universities are increasingly offering support services for bibliometrics, often based in the library. This paper describes work done to produce a competency model for those supporting bibliometrics. The results of a questionnaire in which current practitioners rated bibliometric tasks as entry level, core or specialist are reported. Entry level competencies identified were explaining bibliometric concepts, doing basic calculations and some professional skills. Activities identified by participants as core are outlined. Reflecting on items that were considered in scope but specialist there was less stress on evaluating scholars, work at a strategic level, working with data outside proprietary bibliometric tools and consultancy-type services as opposed to training for disintermediated use. A competency model is presented as an appendix.}, language = {en}, number = {3}, urldate = {2024-08-14}, journal = {Journal of Librarianship and Information Science}, author = {Cox, Andrew and Gadd, Elizabeth and Petersohn, Sabrina and Sbaffi, Laura}, month = sep, year = {2019}, pages = {746--762}, file = {1-s2.0-S0099133321000884-main.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\ZTID5PVK\\1-s2.0-S0099133321000884-main.pdf:application/pdf;Cox et al. - 2019 - Competencies for bibliometrics.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\8BIHXZ6D\\Cox et al. - 2019 - Competencies for bibliometrics.pdf:application/pdf}, } @article{sugimoto_scientific_2021, title = {Scientific success by numbers}, volume = {593}, copyright = {https://www.springer.com/tdm}, issn = {0028-0836, 1476-4687}, url = {https://www.nature.com/articles/d41586-021-01169-7}, doi = {10.1038/d41586-021-01169-7}, language = {en}, number = {7857}, urldate = {2024-08-14}, journal = {Nature}, author = {Sugimoto, Cassidy R.}, month = may, year = {2021}, pages = {30--31}, file = {Sugimoto - 2021 - Scientific success by numbers.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\NBFTN7NY\\Sugimoto - 2021 - Scientific success by numbers.pdf:application/pdf}, } @article{zakaria_data_2021, title = {Data visualization as a research support service in academic libraries: {An} investigation of world-class universities}, volume = {47}, issn = {00991333}, shorttitle = {Data visualization as a research support service in academic libraries}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0099133321000884}, doi = {10.1016/j.acalib.2021.102397}, abstract = {This study aims to shed light on the data visualization services (DVS) provided online by the academic libraries of world-class universities. Thirty library websites from the top 100 universities listed in the QS World University Rankings 2021 were selected for this study. The university library websites were examined and were visited many times for gathering data. The results obtained showed that DVS can be divided into five aspects: infor­ mation, services, training, tools and software, and information resources. Most libraries (93.3\%) offered data visualization tools and software such as Tableau, R, Excel, Gephi, and Plotly. Twenty-six libraries (86.67\%) provided information resources related to data visualization such as textbooks, data sources, external links to eresources, and blogs. Moreover, 80\% of the libraries offered DVS to the university community through their webpages. The findings of this study can help academic libraries improve DVS and draw the attention of libraries worldwide toward providing DVS in the future.}, language = {en}, number = {5}, urldate = {2024-08-15}, journal = {The Journal of Academic Librarianship}, author = {Zakaria, Mahmoud Sherif}, month = sep, year = {2021}, pages = {102397}, file = {Zakaria - 2021 - Data visualization as a research support service i.pdf:C\:\\Users\\guillemi\\Zotero\\storage\\X6YB6I4M\\Zakaria - 2021 - Data visualization as a research support service i.pdf:application/pdf}, }