Large-scale identification and characterization of scholars on Twitter

Abstract

This paper presents a new method for identifying scholars who have a Twitter account from bibliometric data from Web of Science (WoS) and Twitter data from Altmetric.com. The method reliably identifies matches between Twitter accounts and scholarly authors. It consists of a matching of elements such as author names, usernames, handles, and URLs, followed by a rule-based scoring system that weights the common occurrence of these elements related to the activities of Twitter users and scholars. The method proceeds by matching the Twitter accounts against a database of millions of disambiguated bibliographic profiles from WoS. This paper describes the implementation and validation of the matching method, and performs verification through precision-recall analysis. We also explore the geographical, disciplinary, and demographic variations in the distribution of scholars matched to a Twitter account. This approach represents a step forward in the development of more advanced forms of social media studies of science by opening up an important door for studying the interactions between science and social media in general, and for studying the activities of scholars on Twitter in particular.

Publication
Quantitative Science Studies
Rodrigo Costas
Rodrigo Costas
Senior Researcher, Centre for Science and Technology Studies (CWTS)
Philippe Mongeon
Philippe Mongeon
Assistant Professor, School of Information Management, Dalhousie University

I am an assistant professor at the School of Information Management at Dalhousie University, director of the Quantitative Science Studies Lab, and associate member of the Centre interuniversitaire de recherche sur la science et la technologie (CIRST).