Visualizing readership activity of Mendeley users using VOSviewer
Zohreh Zahedi & Nees Jan van EckCenter for Science and Technology Studies (CWTS-Leiden University)
23 June 2014
Introduction
• Mendeley: one of the most important altmetric tools
• For publications in Mendeley readerships statistics are available
• ‘Type of users’ of the Mendeley readerships are available for readerships & publications• Possibility of different types of impact• Readership habits across types of users
• But, with the limitation: Mendeley only reports the 3 ‘top’ frequent types of users per publication
Research questions
• What are the differences in readership activity across research fields?• In which fields are Mendeley users most and
least active?• What are the fields of interest for the different
‘known’ users?• Are there differences?
Methodology
• All 2011 WoS articles & reviews with a DOI• 1,114,776 publications (citations counted up to
2013)
• Readerships statistics collected through the REST API• 847,587 (76%) saved in Mendeley• 438,399 (52%) all the readers were known
• VOS viewer for overlay visualizations• 250 JCR subject categories• Terms from titles & abstracts
Readerships by subject categoryReaderships/publication
Readerships/Citation
Areas with higher readerships per publication:- Cell biology- Biomedical sciences- Multidiscisciplinary- Neurosciences- Business & management
Readership activity vs. citation activity:- Social Sciences- Humanities
Social sciences & humanitiesLit. & pol. science
Cognitive psychology
Marketing & innovation
General medicine topics
Readerships: PhDs vs. ProfessorsOnly papers with known users (52%)
PhDs:- Chemistry- Engineering
(PhDs/all PhDs)(Readerships/all readerships)
Professors:- Mathematics, applied- Political science- Statistics & probability
(Prof./all Profs.)(Readerships/all readerships)
Conclusions
• Mendeley: rich source of altmetric information
• Disciplinary differences in readership activity: biomedical sciences, life sciences and social sciences
• Differences among ‘Mendeley’ users across disciplines• Future research: understand better these differences• Data problems, distribution of users by fields, genuine
content differences, etc.
Thank you very much for your attention!
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