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Citation data for institutes are generally provided as numbers of citations or as relative citation rates (as, for example, in the Leiden Ranking). These numbers can then be compared between the institutes. This study aims to present a new approach for the evaluation of citation data at the institutional level, based on regression models. As example data, the study includes all articles and reviews from the Web of Science for the publication year 2003 ( n = 886,416 papers). The study is based on an in-house database of the Max Planck Society. The study investigates how much the expected number of citations for a publication changes if it contains the address of an institute. The calculation of the expected values allows, on the one hand, investigating how the citation impact of the papers of an institute appears in comparison with the total of all papers. On the other hand, the expected values for several institutes can be compared with one another or with a set of randomly selected publications. Besides the institutes, the regression models include factors which can be assumed to have a general influence on citation counts (e.g., the number of authors). [ABSTRACT FROM AUTHOR]

Citation counts are widely used as indicators of research quality to support or replace human peer review and for lists of top cited papers, researchers, and institutions. Nevertheless, the relationship between citations and research quality is poorly evidenced. We report the first large‐scale science‐wide academic evaluation of the relationship between research quality and citations (field normalized citation counts), correlating them for 87,739 journal articles in 34 field‐based UK Units of Assessment (UoA). The two correlate positively in all academic fields, from very weak (0.1) to strong (0.5), reflecting broadly linear relationships in all fields. We give the first evidence that the correlations are positive even across the arts and humanities. The patterns are similar for the field classification schemes of Scopus and Dimensions.ai, although varying for some individual subjects and therefore more uncertain for these. We also show for the first time that no field has a citation threshold beyond which all articles are excellent quality, so lists of top cited articles are not pure collections of excellence, and neither is any top citation percentile indicator. Thus, while appropriately field normalized citations associate positively with research quality in all fields, they never perfectly reflect it, even at high values. [ABSTRACT FROM AUTHOR]

The large multidisciplinary academic social website ResearchGate aims to help academics to connect with each other and to publicize their work. Despite its popularity, little is known about the age and discipline of the articles uploaded and viewed in the site and whether publication statistics from the site could be useful impact indicators. In response, this article assesses samples of ResearchGate articles uploaded at specific dates, comparing their views in the site to their Mendeley readers and Scopus-indexed citations. This analysis shows that ResearchGate is dominated by recent articles, which attract about three times as many views as older articles. ResearchGate has uneven coverage of scholarship, with the arts and humanities, health professions, and decision sciences poorly represented and some fields receiving twice as many views per article as others. View counts for uploaded articles have low to moderate positive correlations with both Scopus citations and Mendeley readers, which is consistent with them tending to reflect a wider audience than Scopus-publishing scholars. Hence, for articles uploaded to the site, view counts may give a genuinely new audience indicator. [ABSTRACT FROM AUTHOR]

Research collaboration is promoted by governments and research funders, but if the relative prevalence and merits of collaboration vary internationally then different national and disciplinary strategies may be needed to promote it. This study compares the team size and field normalized citation impact of research across all 27 Scopus broad fields in the 10 countries with the most journal articles indexed in Scopus 2008–2012. The results show that team size varies substantially by discipline and country, with Japan (4.2) having two‐thirds more authors per article than the United Kingdom (2.5). Solo authorship is rare in China (4%) but common in the United Kingdom (27%). While increasing team size associates with higher citation impact in almost all countries and fields, this association is much weaker in China than elsewhere. There are also field differences in the association between citation impact and collaboration. For example, larger team sizes in the Business, Management & Accounting category do not seem to associate with greater research impact, and for China and India, solo authorship associates with higher citation impact in this field. Overall, there are substantial international and field differences in the extent to which researchers collaborate and the extent to which collaboration associates with higher citation impact. [ABSTRACT FROM AUTHOR]

The impact of university rankings has driven scholars to increase productivity, and expanding collaboration has dramatically changed the publishing patterns in the academic publication system. The aim of this study was to develop a scholar classification scheme from publication patterns in academic science. Classification schemes are ways of describing groups that display different clusters of behaviors, approaches, or perspectives, and useful in the development of typologies. In this research, sample data are selected from three representative universities, considered a leading university, a middle‐tier university, and a noncomprehensive university. A final set of 11,427 effective scholars and their 284,128 journal publication records were used to develop the classification scheme via cluster analysis. The results identify six types of scholars, labeled as: singleton (8%), small‐team low performer (16%), small‐team high performer (17%), big‐team strategist (22%), free‐style follower (21%), and life‐time warrior (17%). These six scholar types demonstrate different approaches to publishing that can be used to understand both individual and research team performance across different institutional settings. Additionally, possible future work was identified that uses the scholar classification scheme to define the behavior for agents in an agent‐based model to simulate the strategic‐behavior‐driven academic publication system. [ABSTRACT FROM AUTHOR]

Statistics are essential to many areas of research and individual statistical techniques may change the ways in which problems are addressed as well as the types of problems that can be tackled. Hence, specific techniques may tend to generate high-impact findings within science. This article estimates the citation advantage of a technique by calculating the average citation rank of articles using it in the issue of the journal in which they were published. Applied to structural equation modeling ( SEM) and four related techniques in 3 broad fields, the results show citation advantages that vary by technique and broad field. For example, SEM seems to be more influential in all broad fields than the 4 simpler methods, with one exception, and hence seems to be particularly worth adding to statistical curricula. In contrast, Pearson correlation apparently has the highest average impact in medicine but the least in psychology. In conclusion, the results suggest that the importance of a statistical technique may vary by discipline and that even simple techniques can help to generate high-impact research in some contexts. [ABSTRACT FROM AUTHOR]

Little detailed information is known about who reads research articles and the contexts in which research articles are read. Using data about people who register in Mendeley as readers of articles, this article explores different types of users of Clinical Medicine, Engineering and Technology, Social Science, Physics, and Chemistry articles inside and outside academia. The majority of readers for all disciplines were PhD students, postgraduates, and postdocs but other types of academics were also represented. In addition, many Clinical Medicine articles were read by medical professionals. The highest correlations between citations and Mendeley readership counts were found for types of users who often authored academic articles, except for associate professors in some sub-disciplines. This suggests that Mendeley readership can reflect usage similar to traditional citation impact if the data are restricted to readers who are also authors without the delay of impact measured by citation counts. At the same time, Mendeley statistics can also reveal the hidden impact of some research articles, such as educational value for nonauthor users inside academia or the impact of research articles on practice for readers outside academia. [ABSTRACT FROM AUTHOR]