Identifying topics of interest of Mendeley users using the text mining and overlay visualization functionality of VOSviewer

This paper presents the results of a study in which we have analysed the topics of interest of Mendeley users (i.e. Students, PhDs, Post Docs, Researchers, Professors, Librarians, Lecturers & other Professionals) using text mining and visualization techniques. Beside analyzing topics of interest of Mendeley users, we have also identified fields of science for which readership information can be an interesting source of information complementary to citation information. For this purpose, we have used WoS citation data and Mendeley readership data for a set of 980,698 WoS publications (articles and reviews) with a DOI from 20111.The VOSviewer software tool (Van Eck & Waltman, 2010) was used to create so-called overlay visualizations. These visualizations show additional information on top of a base map. Two types of base maps were used. A base map containing the 250 WoS subject categories was used to analyze differences in readership activity across research fields and to analyze differences in interest between types of users. Base maps containing terms extracted from titles and abstracts using the text mining functionality of VOSviewer (Van Eck & Waltman, 2011) were used to analyze differences in readership activity within research fields. Merit, Expertise and Measuremen