Mendeley reader counts for US computer science conference papers and journal articles

Thelwall, Mike

doi:10.1162/qss_a_00010

Cited by 18 publications

(23 citation statements)

References 53 publications

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“…A significant strong positive correlation (where r R > 0.6) was observed between the Dimensions citation and Mendeley readership counts for all the three categories (Figures 1-3). This strong correlation was observed as "Mendeley counts appear about a year before citations typically starting with the publication month of an article, allowing evaluations to be conducted more promptly" (Thelwall, 2020). Furthermore, another reason of getting a strong correlation between Dimensions citation and Mendeley counts would be that Mendeley's users are predominantly academics or doctoral students which usually results in moderate or strong correlation between Mendeley and citation counts in most of the fields (Costas et al, 2015;Haustein et al, 2014;Thelwall, 2017;Aduku et al, 2017;Zahedi and Haustein, 2018;Lamba, 2020).…”

Section: Rankmentioning

confidence: 99%

“…Furthermore, another reason of getting a strong correlation between Dimensions citation and Mendeley counts would be that Mendeley's users are predominantly academics or doctoral students which usually results in moderate or strong correlation between Mendeley and citation counts in most of the fields (Costas et al, 2015;Haustein et al, 2014;Thelwall, 2017;Aduku et al, 2017;Zahedi and Haustein, 2018;Lamba, 2020). Thus, Mendeley readership counts could reasonably be used as impact indicators for journal articles in the field of computer science (Thelwall, 2020). Moreover, the correlation values between Dimensions citations and aggregated Altmetric attention scores increased from negligible (r R = 0.07) for 669 articles to moderate (r R = 0.3) for top 50% of the articles.…”

Section: Rankmentioning

confidence: 99%

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Research evaluation of computer science publications using Altmetrics: a cohort study of Indian Central Universities

Lamba

Kashyap

Madhusudhan

2021

GKMC

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Purpose Social interaction applications and reference tools are actively used by researchers to share and manage their research publications. Thus, this paper aims to determine the scholarly impact of selected Indian central universities. Design/methodology/approach This study analyzed 669 articles having both Dimensions citations and Altmetric attention scores published by 35 Indian central universities for 4 subfields of Computer Science using Altmetric Explorer. This paper determined each university’s contribution in the studied subfields of Computer Science and the correlation among Altmetric attention score (aggregated and individual), Dimensions citation, and Mendeley readership counts for all 669 articles and stratified percentile sets of top 25%, and top 50% of the overall number of articles. Findings The findings showed that Jawaharlal Nehru University had the maximum Altmetric attention score, Banaras Hindu University received the maximum Dimensions citation, and University of Hyderabad (UoH) received the maximum number of Mendeley readers. Each central university was examined individually and then ranked based on their median values of Dimensions citations and Altmetric attention scores. Further, Twitter had the maximum Altmetric coverage, followed by Google+, Patent and Facebook for the retrieved articles. A significant strong positive correlation was observed between the Dimensions citation and Mendeley readership counts for all the three categories. Research limitations/implications Both Altmetric attention scores and Dimensions citations can help funding agencies to assess and evaluate the research productivity of these universities, thus, making important decisions such as increasing, decreasing, re-distributing their funds. Originality/value The current body of research is focused mostly on relationships between citations and individual Altmetric indicators predominantly. For most of the studies, the citations were retrieved from Scopus, Web of Science or Google Scholar database. It was observed that by far, no study had examined the relationship between citations retrieved from Dimensions database, Altmetrics scores (both aggregated and individual) and Mendeley readership counts.

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Section: Rankmentioning

confidence: 99%

Section: Rankmentioning

confidence: 99%

Research evaluation of computer science publications using Altmetrics: a cohort study of Indian Central Universities

Lamba

Kashyap

Madhusudhan

2021

GKMC

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“…The study shows that top conferences make up 30 % of top-quartile publications. Thelwall [30] compares Scopus citations with Mendeley reader counts for conference papers and journal articles in eleven computing subfields showing high correlations between both counts. Kochetkov et al [31] applies a methodology similar to that of SJR to rank conferences in Computer Science.…”

Section: Related Workmentioning

confidence: 99%

Differences in Citation Patterns across Areas, Article Types and Age Groups of Researchers

Mendoza¹

2021

Preprint

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The evaluation of research proposals and academic careers is subject to indicators of scientific productivity. Citations are critical signs of impact for researchers, and many indicators are based on these data. The literature shows that there are differences in citation patterns between areas. The scope and depth that these differences may have to motivate the extension of these studies considering types of articles and age groups of researchers. In this work, we conducted an exploratory study to elucidate what evidence there is about the existence of these differences in citation patterns. To perform this study, we collected historical data from Scopus. Analyzing these data, we evaluate if there are measurable differences in citation patterns. This study shows that there are evident differences in citation patterns between areas, types of publications, and age groups of researchers that may be relevant when carrying out researchers’ academic evaluation.

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“…Early Mendeley readers correlate positively with longer term citations so they can be used to predict eventual citation counts (Thelwall & Nevill, 2018;Thelwall, 2018). Mendeley readers can also be useful for conference papers in fields where they are important (Thelwall, 2020), and are useful, but less prevalent, for books and dissertations (Kousha & Thelwall, 2019).…”

Section: Mendeley Readersmentioning

confidence: 99%

The Pros and Cons of the Use of Altmetrics in Research Assessment

Thelwall¹

2020

SAR

Self Cite

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Many indicators derived from the web have been proposed to supplement citation-based indicators in support of research assessments. These indicators, often called altmetrics, are available commercially from Altmetric.com and Elsevier's Plum Analytics or can be collected directly. These organisations can also deliver altmetrics to support institutional self-evaluations. The potential advantages of altmetrics for research evaluation are that they may reflect important non-academic impacts and may appear before citations when an article is published, thus providing earlier impact evidence. Their disadvantages often include susceptibility to gaming, data sparsity, and difficulties translating the evidence into specific types of impact. Despite these limitations, altmetrics have been widely adopted by publishers, apparently to give authors, editors and readers insights into the level of interest in recently published articles. This article summarises evidence for and against extending the adoption of altmetrics to research evaluations. It argues that whilst systematically-gathered altmetrics are inappropriate for important formal research evaluations, they can play a role in some other contexts. They can be informative when evaluating research units that rarely produce journal articles, when seeking to identify evidence of novel types of impact during institutional or other self-evaluations, and when selected by individuals or groups to support narrative-based non-academic claims. In addition, Mendeley reader counts are uniquely valuable as early (mainly) scholarly impact indicators to replace citations when gaming is not possible and early impact evidence is needed. Organisations using alternative indicators need recruit or develop in-house expertise to ensure that they are not misused, however. Policy highlightsAltmetrics, or alternative indicators for research outputs, have been proposed as a partial solution to two research management problems: (a) assessing the societal impacts of research, and (b) obtaining early impact evidence. This article reviews the evidence and finds limited support for (a) but strong support for (b). Organisations will need to assess whether the value provided by alternative indicators in terms of helping to provide data so support research assessments is sufficient for their financial and time costs. Those using alternative indicators will deed to develop in-house expertise so that they can be used responsibly and interpreted effectively.

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Mendeley reader counts for US computer science conference papers and journal articles

Cited by 18 publications

References 53 publications

Research evaluation of computer science publications using Altmetrics: a cohort study of Indian Central Universities

Research evaluation of computer science publications using Altmetrics: a cohort study of Indian Central Universities

Differences in Citation Patterns across Areas, Article Types and Age Groups of Researchers

The Pros and Cons of the Use of Altmetrics in Research Assessment

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