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Social media has given way for the development of various new altmetric indicators. Mendeley readership count is one such indicator. The purpose of this paper is twofold. First, the paper aims to investigate the relationship between citation counts and Mendeley readership counts. The paper also evaluates the relationship between Mendeley readership metrics for two different time periods, thereby investigating its nature as an altmetric indicator.

Data were collected using the Scopus database. Top 100 papers in Physics published during 2005 as well as in 2010 that received the largest number of citations were selected. Mendeley readership data were collected using Mendeley readership statistics for documents indexed in Scopus. For establishing a relationship between citation counts and Mendeley readership, correlation was calculated between the citations in Scopus database and Mendeley readership. The difference in Mendeley readership for different time periods was also investigated.

The paper showed that for both the years, Mendeley readership counts were in positive correlation with citation counts. For the year 2010, it was found that Mendeley readership counts were in strong positive correlation with citation counts, whereas for 2005, they were in moderate positive correlation.

One of the limitations of this paper is that with time more scientists and researchers may join Mendeley causing various changes in data and giving different results. Also, the paper has focused on the highly cited papers in Physics.

Very few studies have been conducted in the area of altmetrics, as it is a comparatively new and emerging field of research. The findings of this paper offer insights to the question whether Mendeley readership counts can be used as an alternative to traditional sources of bibliometric indicators like citations, h-index, etc. The paper also evaluates the difference in the nature of traditional bibliometric indicators and Mendeley readership counts.

The purpose of this study is to investigate the relationship of the post-publication peer review (PPPR) polarity of a paper to that paper's citation count.

Papers with PPPRs from Publons.com as the experimental groups were manually matched 1:2 with the related papers without PPPR as the control group, by the same journal, the same issue (volume), the same access status (gold open access or not) and the same document type. None of the papers in the experimental group or control group received any comments or recommendations from ResearchGate, PubPeer or F1000. The polarity of the PPPRs was coded by using content analysis. A negative binomial regression analysis was conducted to examine the data by controlling the characteristics of papers.

The four experimental groups and their corresponding control groups were generated as follows: papers with neutral PPPRs, papers with both negative and positive PPPRs, papers with negative PPPRs and papers with positive PPPRs as well as four corresponding control groups (papers without PPPRs). The results are as follows: while holding the other variables (such as page count, number of authors, etc.) constant in the model, papers that received neutral PPPRs, those that received negative PPPRs and those that received both negative and positive PPPRs had no significant differences in citation count when compared to their corresponding control pairs (papers without PPPRs). Papers that received positive PPPRs had significantly greater citation count than their corresponding control pairs (papers without PPPRs) while holding the other variables (such as page count, number of authors, etc.) constant in the model.

Based on a broader range of PPPR sentiments, by controlling many of the confounding factors (including the characteristics of the papers and the effects of the other PPPR platforms), this study analyzed the relationship of various polarities of PPPRs to citation count.

The purpose of this paper is to evaluate the impact of scientific data in order to assess the reliability of data to support data curation, to establish trust between researchers to support reuse of digital data and encourage researchers to share more data.

The authors compared the correlations between usage counts of associated data in Dryad and citation counts of articles in Web of Science in different subject areas in order to assess the possibility of using altmetric indicators to evaluate scientific data.

There are high positive correlations between usage counts of data and citation counts of associated articles. The citation counts of article’s shared data are higher than the average citation counts in most of the subject areas examined by the authors.

The paper suggests that usage counts of data could be potentially used to evaluate scholarly impact of scientific data, especially for those subject areas without special data repositories.

The study examines the possibility to use usage counts to evaluate the impact of scientific data in a generic repository Dryad by different subject categories.

The purpose of this paper is to clarify some issues regarding citation indexing, analysis and searching.

The paper begins with a discussion on an article in the D‐Lib Magazine and then focuses on deflated citation counts and inflated and phantom citation counts.

The combination of the inflated citation count values dispensed by Google Scholar (GS) with the ignorance and shallowness of some GS enthusiasts can be a real mix for real scholars.

The paper offers insight into deflated, inflated and phantom citation counts.

Link analysis is an established topic within webometrics. It normally uses counts of links between sets of web sites or to sets of web sites. These link counts are derived from web crawlers or commercial search engines with the latter being the only alternative for some investigations. This paper compares link counts with URL citation counts in order to assess whether the latter could be a replacement for the former if the major search engines withdraw their advanced hyperlink search facilities.

URL citation counts are compared with link counts for a variety of data sets used in previous webometric studies.

The results show a high degree of correlation between the two but with URL citations being much less numerous, at least outside academia and business.

The results cover a small selection of 15 case studies and so the findings are only indicative. Significant differences between results indicate that the difference between link counts and URL citation counts will vary between webometric studies.

Should link searches be withdrawn, then link analyses of less well linked non‐academic, non‐commercial sites would be seriously weakened, although citations based on e‐mail addresses could help to make citations more numerous than links for some business and academic contexts.

This is the first systematic study of the difference between link counts and URL citation counts in a variety of contexts and it shows that there are significant differences between the two.

A citation study of the 692 staff that makes up unit of assessment 58 (archaeology), in the 2001 UK Research Assessment Exercise (RAE) was undertaken. Unlike earlier studies, which were obliged to make assumptions on who and what had been submitted for assessment, these were, for the first time available from the RAE Web site. This study, therefore, used the specific submission details of authors and their publications. Using the Spearman rank‐order correlation coefficient, all results showed high statistically significant correlation between the RAE result and citation counts. The results were significant at 0.01 per cent. The findings confirm earlier studies. Given the comparative cost and ease of citation analysis, it is recommended that, correctly applied, it should be the initial tool of assessment for the RAE. Panel members would then exercise their judgement and skill to confirm final rankings.

By analyzing journal articles with high citation counts but low Twitter mentions and vice versa, the purpose of this paper is to provide an overall picture of differences between citation counts and Twitter mentions of academic articles.

Citation counts from the Web of Science and Twitter mentions of psychological articles under the Social Science Citation Index collection were collected for data analysis. An approach combining both statistical and simple content analysis was adopted to examine important factors contributing to citation counts and Twitter mentions, as well as the patterns of tweets mentioning academic articles.

Compared to citation counts, Twitter mentions have stronger affiliations with readability and accessibility of academic papers. Readability here was defined as the content size of articles and the usage of jargon and scientific expressions. In addition, Twitter activities, such as the use of hashtags and user mentions, could better facilitate the sharing of articles. Even though discussions of articles or related social phenomena were spotted in the contents of tweets, simple counts of Twitter mentions may not be reliable enough for research evaluations due to issues such as Twitter bots and a deficient understanding of Twitter users’ motivations for mentioning academic articles on Twitter.

This study has elaborated on the differences between Twitter mentions and citation counts by comparing the characteristics of Twitter-inclined and citation-inclined articles. It provides useful information for interested parties who would like to adopt social web metrics such as Twitter mentions as traces of broader engagement with academic literature and potential suggestions to increase the reliability of Twitter metrics. In addition, it gives specific tips for researchers to increase research visibility and get attention from the general public on Twitter.

The purpose of the study is to use a multidimensional perspective on the analysis of scholarly articles published in the top-tier Library and Information Science (LIS) journals. The relationships between the impact factors (Altmetric attention score [AAS], citation count and Mendeley readership) were analyzed, and reader profiles were characterized and studied.

This paper examined citation count, AAS and Mendeley readership of the most cited articles published in the top-tier LIS journals – The Journal of Academic Librarianship, Government Information Quarterly and Library and Information Science Research. A total of 61 articles were analyzed. Data were recorded on an Excel spreadsheet and exported to the statistical software package SPSS 18.0 for Windows to perform the descriptive and correlation analysis.

This study suggests that Mendeley readership and AAS could be used as supplemental measurements for assessing the impact of a publication or author in the LIS. AAS and Mendeley readership are positively correlated with citation count, and the correlation between Mendeley readership and citation count was stronger than AAS and citation count. Librarians are dominant readers of the top-tier LIS journals, followed by social sciences, computer science and arts and humanities professions.

This study introduces two newly launched metrics for measuring the research impact factor and discusses how they correlated with citation count. Moreover, the study details the spectrum of Altmetric for discovering readership of LIS top-tier journals. To the best of authors’ knowledge, this is the first study that presents the spectrum of AAS and Mendeley readership of the most cited articles published in top-tier of LIS journals. The study reveals an alternative way of measuring LIS publication’s impact factor that enables researchers, librarians, administrators, publishers and other stakeholders in LIS to assess the influence of a publication from another angle.

A study was carried out to assess the correlation between scores achieved by academic departments in the UK in the 1992 Research Assessment Exercise, and the number of citations received by academics in those departments for articles published in the period 1988±1992, using the Institute for Scientific Information’s citation databases. Only those papers first authored by academics identified from the Commonwealth Universities Yearbook were examined. Three subject areas: Anatomy, Genetics and Archaeology were chosen to complement Library and Information Management that had already been the subject of such a study. It was found that in all three cases, there is a statistically significant correlation between the total number of citations received, or the average number of citations per member of staff, and the Research Assessment Exercise score. Surprisingly, the strongest correlation was found in Archaeology, a subject noted for its heavy emphasis on monographic literature and with relatively low citation counts. The results make it clear that citation counting provides a robust and reliable indicator of the research performance of UK academic departments in a variety of disciplines, and the paper argues that for future Research Assessment Exercises, citation counting should be the primary, but not the only, means of calculating Research Assessment Exercise scores.

A citation study was carried out on all 217 academics who teach in UK library and information science schools. These authors between them received 622 citations in Social Scisearch for articles they had published between 1988 and the present. The results were ranked by department, and compared to the ratings awarded to the departments in the 1992 Universities Funding Council Research Assessment Exercise. Using the Spearman Rank Order Correlation coefficient, it was found that there is a statistically significant correlation between the numbers of citations received by a department in total, or the average number of citations received in the department per academic, and the Research Assessment Exercise rating. The paper concludes that this provides further independent support for the validity of citation counting, even when using just the first authors as a search tool for cited references. The paper also concludes that the cost and effort of the Research Assessment Exercise may not be justified when a simpler and cheaper alternative, namely a citation counting exercise, could be undertaken. The paper also concludes that the University of North London would probably have benefitted from being included in the 1992 Research Assessment Exercise.