Search (358 results, page 18 of 18)

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Abstract

This study presents a large-scale analysis of the distribution and presence of Mendeley readership scores over time and across disciplines. We study whether Mendeley readership scores (RS) can identify highly cited publications more effectively than journal citation scores (JCS). Web of Science (WoS) publications with digital object identifiers (DOIs) published during the period 2004-2013 and across five major scientific fields were analyzed. The main result of this study shows that RS are more effective (in terms of precision/recall values) than JCS to identify highly cited publications across all fields of science and publication years. The findings also show that 86.5% of all the publications are covered by Mendeley and have at least one reader. Also, the share of publications with Mendeley RS is increasing from 84% in 2004 to 89% in 2009, and decreasing from 88% in 2010 to 82% in 2013. However, it is noted that publications from 2010 onwards exhibit on average a higher density of readership versus citation scores. This indicates that compared to citation scores, RS are more prevalent for recent publications and hence they could work as an early indicator of research impact. These findings highlight the potential and value of Mendeley as a tool for scientometric purposes and particularly as a relevant tool to identify highly cited publications.

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Abstract

In this article, we investigate the consequences of choosing different classification systems-namely, the way publications (or journals) are assigned to scientific fields-for the ranking of research units. We study the impact of this choice on the ranking of 500 universities in the 2013 edition of the Leiden Ranking in two cases. First, we compare a Web of Science (WoS) journal-level classification system, consisting of 236 subject categories, and a publication-level algorithmically constructed system, denoted G8, consisting of 5,119 clusters. The result is that the consequences of the move from the WoS to the G8 system using the Top 1% citation impact indicator are much greater than the consequences of this move using the Top 10% indicator. Second, we compare the G8 classification system and a publication-level alternative of the same family, the G6 system, consisting of 1,363 clusters. The result is that, although less important than in the previous case, the consequences of the move from the G6 to the G8 system under the Top 1% indicator are still of a large order of magnitude.

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Abstract

Purpose Chemical databases have had a significant impact on the way scientists search for and use information. The purpose of this paper is to spark informed discussion and fuel debate on the issue of citations to chemical databases. Design/methodology/approach A citation analysis to four major chemical databases was undertaken to examine resource coverage and impact in the scientific literature. Two commercial databases (SciFinder and Reaxys) and two public databases (PubChem and ChemSpider) were analyzed using the "Cited Reference Search" in the Science Citation Index Expanded from the Web of Science (WoS) database. Citations to these databases between 2000 and 2016 (inclusive) were evaluated by document types and publication growth curves. A review of the distribution trends of chemical databases in peer-reviewed articles was conducted through a citation count analysis by country, organization, journal and WoS category. Findings In total, 862 scholarly articles containing a citation to one or more of the four databases were identified as only steadily increasing since 2000. The study determined that authors at academic institutions worldwide reference chemical databases in high-impact journals from notable publishers and mainly in the field of chemistry. Originality/value The research is a first attempt to evaluate the practice of citation to major chemical databases in the scientific literature. This paper proposes that citing chemical databases gives merit and recognition to the resources as well as credibility and validity to the scholarly communication process and also further discusses recommendations for citing and referencing databases.

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Abstract

Theory is a kind of condensed human knowledge. This paper is to examine the mechanism of interdisciplinary diffusion of theoretical knowledge by tracing the diffusion of a representative theory, the Technology Acceptance Model (TAM). Design/methodology/approach Based on the full-scale dataset of Web of Science (WoS), the citations of Davis's original work about TAM were analysed and the interdisciplinary diffusion paths of TAM were delineated, a supervised machine learning method was used to extract theory incidents, and a content analysis was used to categorize the patterns of theory evolution. Findings It is found that the diffusion of a theory is intertwined with its evolution. In the process, the role that a participating discipline play is related to its knowledge distance from the original disciplines of TAM. With the distance increases, the capacity to support theory development and innovation weakens, while that to assume analytical tools for practical problems increases. During the diffusion, a theory evolves into new extensions in four theoretical construction patterns, elaboration, proliferation, competition and integration. Research limitations/implications The study does not only deepen the understanding of the trajectory of a theory but also enriches the research of knowledge diffusion and innovation. Originality/value The study elaborates the relationship between theory diffusion and theory development, reveals the roles of the participating disciplines played in theory diffusion and vice versa, interprets four patterns of theory evolution and uses text mining technique to extract theory incidents, which makes up for the shortcomings of citation analysis and content analysis used in previous studies.

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Abstract

To provide some context for the potential engagement behavior of Twitter users around science, this article investigates how Bitly short links to scientific publications embedded in scholarly Twitter mentions are clicked on Twitter. Based on the click metrics of over 1.1 million Bitly short links referring to Web of Science (WoS) publications, our results show that around 49.5% of them were not clicked by Twitter users. For those Bitly short links with clicks from Twitter, the majority of their Twitter clicks accumulated within a short period of time after they were first tweeted. Bitly short links to the publications in the field of Social Sciences and Humanities tend to attract more clicks from Twitter over other subject fields. This article also assesses the extent to which Twitter clicks are correlated with some other impact indicators. Twitter clicks are weakly correlated with scholarly impact indicators (WoS citations and Mendeley readers), but moderately correlated to other Twitter engagement indicators (total retweets and total likes). In light of these results, we highlight the importance of paying more attention to the click metrics of URLs in scholarly Twitter mentions, to improve our understanding about the more effective dissemination and reception of science information on Twitter.

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Abstract

Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with individual article quality scores. It exploits expert norm-referenced peer review scores from the UK Research Excellence Framework 2021 for 67,030+ journal articles in all fields 2014-2017/2018, split into 34 broadly field-based Units of Assessment (UoAs). Altmetrics correlated more strongly with research quality than previously found, although less strongly than raw and field normalized Scopus citation counts. Surprisingly, field normalizing citation counts can reduce their strength as a quality indicator for articles in a single field. For most UoAs, Mendeley reader counts are the best altmetric (e.g., three Spearman correlations with quality scores above 0.5), tweet counts are also a moderate strength indicator in eight UoAs (Spearman correlations with quality scores above 0.3), ahead of news (eight correlations above 0.3, but generally weaker), blogs (five correlations above 0.3), and Facebook (three correlations above 0.3) citations, at least in the United Kingdom. In general, altmetrics are the strongest indicators of research quality in the health and physical sciences and weakest in the arts and humanities.

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Abstract

The phenomenon of co-corresponding authorship is becoming more and more common. To understand the practice of authorship credit sharing among multiple corresponding authors, we comprehensively analyzed the characteristics of the phenomenon of co-corresponding authorships from the perspectives of countries, disciplines, journals, and articles. This researcher was based on a dataset of nearly 8 million articles indexed in the Web of Science, which provides systematic, cross-disciplinary, and large-scale evidence for understanding the phenomenon of co-corresponding authorship for the first time. Our findings reveal that higher proportions of co-corresponding authorship exist in Asian countries, especially in China. From the perspective of disciplines, there is a relatively higher proportion of co-corresponding authorship in the fields of engineering and medicine, while a lower proportion exists in the humanities, social sciences, and computer science fields. From the perspective of journals, high-quality journals usually have higher proportions of co-corresponding authorship. At the level of the article, our findings proved that, compared to articles with a single corresponding author, articles with multiple corresponding authors have a significant citation advantage.

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Source

Online Mitteilungen. 2004, Nr.79, S.22-23 [=Mitteilungen VÖB 57(2004) H.2]

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Date

20. 3.2005 10:54:22

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Content

Beitrag einer Section "Selected Papers from the 1ST Brazilian Conference on Knowledge Organization And Representation, Faculdade de Ciência da Informação, Campus Universitário Darcy Ribeiro Brasília, DF Brasil, October 20-22, 2011" Vgl.: http://www.ergon-verlag.de/isko_ko/downloads/ko_39_2012_3_g.pdf.

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Date

20. 1.2015 18:30:22

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Date

20. 1.2015 18:30:22

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Abstract

Large national social surveys are expensive to conduct and to process into usable data files. The purpose of this article is to assess the impact of these national data sets on research using bibliometric measures. Peer-reviewed articles from research using numeric data files and documentation from the Canadian National Population Health Survey (NPHS) were searched in ISI's Web of Science and in Scopus for articles citing the original research. This article shows that articles using NPHS data files and products have been used by a diverse and global network of scholars, practitioners, methodologists, and policy makers. Shifts in electronic publishing and the emergence of new tools for citation analysis are changing the discovery process for published and unpublished work based on inputs to the research process. Evidence of use of large surveys throughout the knowledge transfer process can be critical in assessing grant and operating funding levels for research units, and in influencing design, methodology, and access channels in planning major surveys. The project has gathered citations from the peer-reviewed article stage of knowledge transfer, providing valuable evidence on the use of the data files and methodologies of the survey and of limitations of the survey. Further work can be done to expand the scope of material cited and analyze the data to understand how the longitudinal aspect of the survey contributes to the value of the research output. Building a case for continued funding of national, longitudinal surveys is a challenge. As far as I am aware, however, little use has been made of citation tracking to assess the long-term value of such surveys. Conducting citation analysis on research inputs (data file use and survey products) provides a tangible assessment of the value accrued from large-scale (and expensive) national surveys.

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Abstract

Following the transition from print journals to electronic (hybrid) journals in the past decade, usage metrics have become an interesting complement to citation metrics. In this article we investigate the similarities of and differences between usage and citation indicators for pharmacy and pharmacology journals and relate the results to a previous study on oncology journals. For the comparison at journal level we use the classical citation indicators as defined in the Journal Citation Reports and compute the corresponding usage indicators. At the article level we not only relate download and citation counts to each other but also try to identify the possible effect of citations upon subsequent downloads. Usage data were provided by ScienceDirect both at the journal level and, for a few selected journals, on a paper-by-paper basis. The corresponding citation data were retrieved from the Web of Science and Journal Citation Reports. Our analyses show that electronic journals have become generally accepted over the last decade. While the supply of ScienceDirect pharma journals rose by 50% between 2001 and 2006, the total number of article downloads (full-text articles [FTAs]) multiplied more than 5-fold in the same period. This also impacted the pattern of scholarly communication (strong increase in the immediacy index) in the past few years. Our results further reveal a close relation between citation and download frequencies. We computed a high correlation at the journal level when using absolute values and a moderate to high correlation when relating usage and citation impact factors. At the article level the rank correlation between downloads and citations was only medium-sized. Differences between downloads and citations exist in terms of obsolescence characteristics. While more than half of the articles are downloaded in the publication year or 1 year later, the median cited half-life was nearly 6 years for our journal sample. Our attempt to reveal a direct influence of citations upon downloads proved not to be feasible.

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Abstract

This study aims to identify the way researchers collaborate with other researchers in the course of the scientific research life cycle and provide information to the designers of e-Science and e-Research implementations. On the basis of in-depth interviews with and on-site observations of 24 scientists and a follow-up focus group interview in the field of bioscience/nanoscience and technology in Korea, we examined scientific collaboration using the framework of the scientific research life cycle. We attempt to explain the major motiBiochemistry is a highly funded research area that is typified by large research teams and is important for many areas of the life sciences. This article investigates the citation impact and Mendeley readership impact of biochemistry research from 2011 in the Web of Science according to the type of collaboration involved. Negative binomial regression models are used that incorporate, for the first time, the inclusion of specific countries within a team. The results show that, holding other factors constant, larger teams robustly associate with higher impact research, but including additional departments has no effect and adding extra institutions tends to reduce the impact of research. Although international collaboration is apparently not advantageous in general, collaboration with the United States, and perhaps also with some other countries, seems to increase impact. In contrast, collaborations with some other nations seems to decrease impact, although both findings could be due to factors such as differing national proportions of excellent researchers. As a methodological implication, simpler statistical models would find international collaboration to be generally beneficial and so it is important to take into account specific countries when examining collaboration.t only in the beginning phase of the cycle. For communication and information-sharing practices, scientists continue to favor traditional means of communication for security reasons. Barriers to collaboration throughout the phases included different priorities, competitive tensions, and a hierarchical culture among collaborators, whereas credit sharing was a barrier in the research product phase.

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Abstract

Purpose This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011-2020. It also examines changes in this structure from 2006-2010 through 2011-2015 to 2016-2020. Results will contribute to a better understanding of the information science research field. Design/methodology/approach The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011-2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor. Findings The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011-2015 but shared dominance with information behavior during 2016-2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016-2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011-2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016-2020. Originality/value Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

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Content

Vgl. auch Open Password, Nr.167 vom 01.03.2017 :"Eugene Garfield, Begründer und Pionier der Zitationsindexierung und der Ziationsanalyse, ohne den die Informationswissenschaft heute anders aussähe, ist im Alter von 91 Jahren gestorben. Er hinterlässt Frau, drei Söhne, eine Tochter, eine Stieftochter, zwei Enkeltöchter und zwei Großelternkinder. Garfield machte seinen ersten Abschluss als Bachelor in Chemie an der Columbia University in New York City im Jahre 1949. 1954 sattelte er einen Abschluss in Bibliothekswissenschaft drauf. 1961 sollte er im Fach strukturelle Linguistik promovieren. Als Chemie-Student war er nach eigenen Angaben weder besonders gut noch besonders glücklich. Sein "Erweckungserlebnis" hatte er auf einer Tagung der American Chemical Society, als er entdeckte, dass sich mit der Suche nach Literatur womöglich ein Lebensunterhalt bestreiten lasse. "So I went to the Chairman of the meeting and said: "How do you get a job in this racket?" Ab 1955 war Garfield zunächst als Berater für pharmazeutische Unternehmen tätig. Dort spezialisierte er sich auf Fachinformationen, indem er Inhalte relevanter Fachzeitschriften erarbeitete. 1955 schlug er in "Science" seine bahnbrechende Idee vor, Zitationen wissenschaftlicher Veröffentlichungen systematisch zu erfassen und Zusammenhänge zwischen Zitaten deutlich zu machen. 1960 gründete Garfield das Institute für Scientific Informationen, dessen CEO er bis 1992 blieb. 1964 brachte er den Scientific Information Index heraus. Weitere Maßgrößen wie der Social Science Index (ab 1973), der Arts and Humanities Citation Index (ab 1978) und der Journal Citation Index folgten. Diese Verzeichnisse wurden in dem "Web of Science" zusammengefasst und als Datenbank elektronisch zugänglich gemacht. Damit wurde es den Forschern ermöglich, die für sie relevante Literatur "at their fingertips" zu finden und sich in ihr zurechtzufinden. Darüber hinaus wurde es mit Hilfe der Rankings von Garfields Messgrößen möglich, die relative wissenschaftliche Bedeutung wissenschaftlicher Beiträge, Autoren, wissenschaftlicher Einrichtungen, Regionen und Länder zu messen.