Mendeley readership as a filtering tool to identify highly cited publications

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 DOIs published during the period 2004-2013 and across 5 major scientific fields have been analyzed. The main result of this study shows that readership scores are more effective (in terms of precision/recall values) than journal citation scores 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 readership scores 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 vs. citation scores. This indicates that compared to citation scores, readership scores 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

Do Mendeley readership counts help to filter highly cited WoS publications better than average citation impact of journals (JCS)?

In this study, the academic status of users of scientific publications in Mendeley is explored in order to analyse the usage pattern of Mendeley users in terms of subject fields, citation and readership impact. The main focus of this study is on studying the filtering capacity of Mendeley readership counts compared to journal citation scores in detecting highly cited WoS publications. Main finding suggests a faster reception of Mendeley readerships as compared to citations across 5 major field of science. The higher correlations of scientific users with citations indicate the similarity between reading and citation behaviour among these users. It is confirmed that Mendeley readership counts filter highly cited publications (PPtop 10%) better than journal citation scores in all subject fields and by most of user types. This result reinforces the potential role that Mendeley readerships could play for informing scientific and alternative impacts.Comment: This paper presented at the 15th International Conference on Scientometrics and Informetrics (ISSI), 29 Jun-4 July, 2015, Bogazici University, Istanbul (Turkey

COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts

© 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00066The COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indicators during 21 March to 18 April 2020. The rapidly increasing volume of research, is particularly accessible through Dimensions, and less through Scopus, the Web of Science, and PubMed. Google Scholar’s results included many false matches. A few COVID-19 papers from the 21,395 in Dimensions were already highly cited, with substantial news and social media attention. For this topic, in contrast to previous studies, there seems to be a high degree of convergence between articles shared in the social web and citation counts, at least in the short term. In particular, articles that are extensively tweeted on the day first indexed are likely to be highly read and relatively highly cited three weeks later. Researchers needing wide scope literature searches (rather than health focused PubMed or medRxiv searches) should start with Dimensions (or Google Scholar) and can use tweet and Mendeley reader counts as indicators of likely importance

Assessing the Impact of Publications Saved by Mendeley Users: Is There Any Different Pattern Among Users?

The main focus of this paper is to investigate the impact of publications read (saved) by the different users in Mendeley in order to explore the extent to which their readership counts correlate with their citation indicators. The potential of filtering highly cited papers by Mendeley readerships and its different users have been also explored. For the analysis of the users, we have considered the information of the top three Mendeley ‘users’ reported by the Mendeley. Our results show that publications with Mendeley readerships tend to have higher citation and journal citation scores than publications without readerships. ‘Biomedical & health sciences’ and ‘Mathematics and computer science’ are the fields with respectively the most and the least readership activity in Mendeley. PhD students have the highest density of readerships per publication and Lecturers and Librarians have the lowest across all the different fields. Our precision-recall analysis indicates that in general, for publications with at least one reader in Mendeley, the capacity of readerships of filtering highly cited publications is better than (or at least as good as) Journal Citation Scores. We discuss the important limitation of Mendeley of only reporting the top three readers and not all of them in the potential development of indicators based on Mendeley and its users

Altmetrics for Digital Libraries: Concepts, Applications, Evaluation, and Recommendations

The volume of scientific literature is rapidly increasing, which has led to researchers becoming overloaded by the number of articles that they have available for reading and difficulties in estimating their quality and relevance (e.g., based on their research interests). Library portals, in these circumstances, are increasingly getting more relevant by using quality indicators that can help researchers during their research discovery process. Several evaluation methods (e.g., citations, Journal Impact Factor, and peer-reviews) have been used and suggested by library portals to help researchers filter out the relevant articles (e.g., articles that have received high citations) for their needs. However, in some cases, these methods have been criticized, and a number of weaknesses have been identified and discussed. For example, citations usually take a long time to appear, and some articles that are important can remain uncited. With the growing presence of social media today, new alternative indicators, known as “altmetrics,” have been encountered and proposed as complementary indicators to traditional measures (i.e., bibliometrics). They can help to identify the online attention received by articles, which might act as a further indicator for research assessment. One often mentioned advantage of these alternative indicators is, for example, that they appear much faster compared to citations. A large number of studies have explored altmetrics for different disciplines, but few studies have reported about altmetrics in the fields of Economics and Business Studies. Furthermore, no studies can be found so far that analyzed altmetrics within these disciplines with respect to libraries and information overload. Thus, this thesis explores opportunities for introducing altmetrics as new method for filtering relevant articles (in library portals) within the discipline of Economic and Business Studies literature. To achieve this objective, we have worked on four main aspects of investigating altmetrics and altmetrics data, respectively, of which the results can be used to fill the gap in this field of research. (1) We first highlight to what extent altmetric information from the two altmetric providers Mendeley and Altmetric.com is present within the journals of Economics and Business Studies. Based on the coverage, we demonstrate that altmetrics data are sparse in these disciplines, and when considering altmetrics data for real-world applications (e.g., in libraries), higher aggregation levels, such as journal level, can overcome their sparsity well. (2) We perform and discuss the correlations of citations on article and journal levels between different types and sources of altmetrics. We could show that Mendeley counts are positive and strongly correlated with citation counts on both article and journal levels, whereas other indicators such as Twitter counts and Altmetric Attention Score are significantly correlated only on journal level. With these correlations, we could suggest Mendeley counts for Economic and Business Studies journals/articles as an alternative indicator to citations. (3) In conjunction with the findings related to altmetrics in Economics and Business Studies journals, we discuss three use cases derived from three ZBW personas in terms of altmetrics. We investigate the use of altmetrics data for potential users with interests in new trends, social media platforms and journal rankings. (4) We investigated the behavior of economic researchers using a survey by exploring the usefulness of different altmetrics on journal level while they make decisions for selecting one article for reading. According to the user evaluation results, we demonstrate that altmetrics are not well known and understood by the economic community. However, this does not mean that these indicators are not helpful at all to economists. Instead, it brings forward the problem of how to introduce altmetrics to the economic community in the right way using which characteristics (e.g., as visible numbers attached at library records or behind the library’s relevance ranking system). Considering the aforementioned findings of this thesis, we can suggest several forms of presenting altmetric information in library portals, using EconBiz as the proof-of-concept, with the intention to assist both researchers and libraries to identify relevant journals or articles (e.g., highly mentioned online and recently published) for their need and to cope with the information overload

Do altmetrics correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective

An extensive analysis of the presence of different altmetric indicators provided by Altmetric.com across scientific fields is presented, particularly focusing on their relationship with citations. Our results confirm that the presence and density of social media altmetric counts are still very low and not very frequent among scientific publications, with 15%-24% of the publications presenting some altmetric activity and concentrating in the most recent publications, although their presence is increasing over time. Publications from the social sciences, humanities and the medical and life sciences show the highest presence of altmetrics, indicating their potential value and interest for these fields. The analysis of the relationships between altmetrics and citations confirms previous claims of positive correlations but relatively weak, thus supporting the idea that altmetrics do not reflect the same concept of impact as citations. Also, altmetric counts do not always present a better filtering of highly cited publications than journal citation scores. Altmetrics scores (particularly mentions in blogs) are able to identify highly cited publications with higher levels of precision than journal citation scores (JCS), but they have a lower level of recall. The value of altmetrics as a complementary tool of citation analysis is highlighted, although more research is suggested to disentangle the potential meaning and value of altmetric indicators for research evaluation

Mendeley Readership Count: An Investigation of Sambalpur University Publications from 1971-2018

Mendeley offers readership statistic to publications and use these readership statistics to evaluate research performance of an individual. The primary purpose of this paper is to investigate the Mendeley readership counts of Sambalpur University\u27s publications from 1971 to 2018. In this study; bibliographical data exported from Scopus using affiliations search tab and exported data between1971 to 2018. A total of 1553 records were found. The exported data converted into a text file and run in Webometric Analyst software and exported the Mendeley readership data from Mendeley website. A total 1399 record existed in the Mendeley database, in which 173 data have no readership found and further, 1226 publications data analyzed. The readership statistics of Sambalpur University have no impressive growth. Further study found that the yearly growth of Mendeley readership was not stable, and it fluctuated over time. There were positive 0.3303 correlations between Scopus citation and Mendeley readership of the published papers. Mendeley readership statistics by country found that most of the readers are from India, followed by the United States

Altmetrics for Digital Libraries

The volume of scientific literature is increasing and researchers have difficulties in estimating their quality and relevance. Library portals, therefore, are getting more relevant by using quality indicators to help researchers during their research process. With the growing presence of social media, altmetrics have been proposed as complementary indicators to traditional measures. Altmetrics can help to identify online attention and can appear much faster than citations. This study explores altmetrics for filtering relevant articles (in library portals) within the discipline of Economic and Business Studies literature. Firstly, it highlights the altmetrics presence from Mendeley and Altmetric.com for the journals in the above-mentioned disciplines. It presents correlations between citation and altmetrics on article and journal level, suggesting Mendeley counts as an alternative indicator to citations. Afterward, it investigates the use of altmetrics data for potential users with interests in new trends, social media platforms, and journal rankings. Lastly, it explores the behavior of economic researchers using a survey by discovering the usefulness of different altmetrics. With the findings of this study, several forms of altmetrics in library portals are discussed, using EconBiz as the proof-of-concept, to assist both researchers and libraries to identify relevant journals or articles and to cope with the information overload

Social Media Attention Increases Article Visits: An Investigation on Article-Level Referral Data of PeerJ

In order to better understand the effect of social media in the dissemination of scholarly articles, employing the daily updated referral data of 110 PeerJ articles collected over a period of 345 days, we analyze the relationship between social media attention and article visitors directed by social media. Our results show that social media presence of PeerJ articles is high. About 68.18% of the papers receive at least one tweet from Twitter accounts other than @PeerJ, the official account of the journal. Social media attention increases the dissemination of scholarly articles. Altmetrics could not only act as the complement of traditional citation measures but also play an important role in increasing the article downloads and promoting the impacts of scholarly articles. There also exists a significant correlation among the online attention from different social media platforms. Articles with more Facebook shares tend to get more tweets. The temporal trends show that social attention comes immediately following publication but does not last long, so do the social media directed article views