Networks of reader and country status: an analysis of Mendeley reader statistics

Abstract

The number of papers published in journals indexed by the Web of Science core collection is steadily increasing. In recent years, nearly two million new papers were published each year; somewhat more than one million papers when primary research papers are considered only (articles and reviews are the document types where primary research is usually reported or reviewed). However, who reads these papers? More precisely, which groups of researchers from which (self-assigned) scientific disciplines and countries are reading these papers? Is it possible to visualize readership patterns for certain countries, scientific disciplines, or academic status groups? One popular method to answer these questions is a network analysis. In this study, we analyze Mendeley readership data of a set of 1,133,224 articles and 64,960 reviews with publication year 2012 to generate three different networks: (1) The network based on disciplinary affiliations of Mendeley readers contains four groups: (i) biology, (ii) social sciences and humanities (including relevant computer sciences), (iii) bio-medical sciences, and (iv) natural sciences and engineering. In all four groups, the category with the addition "miscellaneous" prevails. (2) The network of co-readers in terms of professional status shows that a common interest in papers is mainly shared among PhD students, Master's students, and postdocs. (3) The country network focusses on global readership patterns: a group of 53 nations is identified as core to the scientific enterprise, including Russia and China as well as two thirds of the OECD (Organisation for Economic Cooperation and Development) countries.

Social Media Metrics for New Research Evaluation

“…These are the least developed and more research will be necessary to fully grasp the possibilities of these analyses. In this section we will just focus on three basic examples of current applications: the analysis of communities of attention (Haustein, Bowman, & Costas, 2015a), hashtag coupling analysis (van Honk & Costas, 2016) and reading/reader pattern analysis (Haunschild, Bornmann, & Leydesdorff, 2015;Kraker, Schlögl, Jack, & Lindstaedt, 2015;Zahedi & Van Eck, 2014).…”

“…Those publications with high co-occurrence in different users' profiles are considered to be more similar in terms of their thematic subject (Kraker, et al, 2015). The network of user groups in Mendeley saving the same set of publications showed that students and postdocs have more common topical interests than other user groups (Haunschild, Bornmann, & Leydesdorff, 2015). Others visualized readership activities and topics of interests of Mendeley users using the text mining functionality of VOSviewer and showed disciplinary differences in readership activity and topical interests (Zahedi & Van Eck, 2015).…”

Mendeley readership as a filtering tool to identify highly cited publications

“…Some other important features of Mendeley are that these readership statistics include data about the academic's status, disciplines and countries of the Mendeley users. This information on the academic's disciplinary and geographic background of the different users helps to better understand the saving patterns of scientific publications by different groups of users Haunschild, Bornmann & Leydesdorff, 2015;Thelwall & Maflahi, 2015). Another important characteristic of this tool is that readership data tend to be collected and made available before citation is recorded by any citation database.…”

“Heterogeneous couplings”: Operationalizing network perspectives to study science‐society interactions through social media metrics

“…Another source of relevant couplings (and network analytical possibilities) come from the online reference manager Mendeley (Haunschild, Bornmann, & Leydesdorff, 2015) in the form of Mendeley users' savings of publications (Zohreh Zahedi, 2018). One of the first proposals that could be related to the idea of heterogeneous couplings was suggested by (Kraker et al, 2015) on the explicit analysis of co‐readership .…”