Profiling Bot Accounts Mentioning COVID-19 Publications on Twitter

Yingxin Estella Ye*, Jin Cheon Na

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents preliminary findings regarding automated bots mentioning scientific papers about COVID-19 publications on Twitter. A quantitative approach was adopted to characterize social and posting patterns of bots, in contrast to other users, in Twitter scholarly communication. Our findings indicate that bots play a prominent role in research dissemination and discussion on the social web. We observed 0.45% explicit bots in our sample, producing 2.9% of tweets. The results implicate that bots tweeted differently from non-bot accounts in terms of the volume and frequency of tweeting, the way handling the content of tweets, as well as preferences in article selection. In the meanwhile, their behavioral patterns may not be the same as Twitter bots in another context. This study contributes to the literature by enriching the understanding of automated accounts in the process of scholarly communication and demonstrating the potentials of bot-related studies in altmetrics research.

Original languageEnglish
Title of host publicationDigital Libraries at Times of Massive Societal Transition - 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings
EditorsEmi Ishita, Natalie Lee Pang, Lihong Zhou
PublisherSpringer Science and Business Media Deutschland GmbH
Pages297-306
Number of pages10
ISBN (Print)9783030644512
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020 - Kyoto, Japan
Duration: Nov 30 2020Dec 1 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12504 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020
Country/TerritoryJapan
CityKyoto
Period11/30/2012/1/20

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Altmetrics research
  • Bot
  • Network analysis
  • Twitter

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