Journal of Data and Information Science ›› 2020, Vol. 5 ›› Issue (3): 5-17.doi: 10.2478/jdis-2020-0017

• Research Papers • Previous Articles     Next Articles

Library and Information Science Papers Discussed on Twitter: A new Network-based Approach for Measuring Public Attention

Robin Haunschild1,(), Loet Leydesdorff2, Lutz Bornmann3   

  1. 1Max Planck Institute for Solid State Research, Heisenbergstr. 1, 70569 Stuttgart, Germany
    2Amsterdam School of Communication Research (ASCoR), University of Amsterdam, PB 15793, 1001 NG Amsterdam, The Netherlands
    3Administrative Headquarters of the Max Planck Society, Division for Science and Innovation Studies, Hofgartenstr. 8, 80539 Munich, Germany;
  • Received:2020-01-21 Revised:2020-05-04 Accepted:2020-05-20 Online:2020-07-20 Published:2020-09-04
  • Contact: Robin Haunschild


Purpose: In recent years, one can witness a trend in research evaluation to measure the impact on society or attention to research by society (beyond science). We address the following question: can Twitter be meaningfully used for the mapping of public and scientific discourses?

Design/methodology/approach: Recently, Haunschild et al. (2019) introduced a new network-oriented approach for using Twitter data in research evaluation. Such a procedure can be used to measure the public discussion around a specific field or topic. In this study, we used all papers published in the Web of Science (WoS, Clarivate Analytics) subject category Information Science & Library Science to explore the publicly discussed topics from the area of library and information science (LIS) in comparison to the topics used by scholars in their publications in this area.

Findings: The results show that LIS papers are represented rather well on Twitter. Similar topics appear in the networks of author keywords of all LIS papers, not tweeted LIS papers, and tweeted LIS papers. The networks of the author keywords of all LIS papers and not tweeted LIS papers are most similar to each other.

Research limitations: Only papers published since 2011 with DOI were analyzed.

Practical implications: Although Twitter data do not seem to be useful for quantitative research evaluation, it seems that Twitter data can be used in a more qualitative way for mapping of public and scientific discourses.

Originality/value: This study explores a rather new methodology for comparing public and scientific discourses.

Key words: Altmetrics, Twitter, News, Hashtags, Author