Altmetrics: “Tweets as Impact Indicators: Examining the Implications of Automated ‘Bot’ Accounts on Twitter”

Here’s a new preprint from researchers in Canada, Finland, and the U.S. that will likely be of interest to many infoDOCKET readers.

Title

Tweets as Impact Indicators: Examining the Implications of Automated “Bot” Accounts on Twitter

Authors

Stefanie Haustein
Université de Montréal

Timothy D. Bowman
Université de Montréal
Kim Holmberg
University of Turku
Andrew Tsou
Indiana University
Cassidy R. Sugimoto
Indiana University
Vincent Larivière
Université du Québec à Montréal
University of Turku

Source

via arXiv

Abstract

This brief communication presents preliminary findings on automated Twitter accounts distributing links to scientific papers deposited on the preprint repository arXiv. It discusses the implication of the presence of such bots from the perspective of social media metrics (altmetrics), where mentions of scholarly documents on Twitter have been suggested as a means of measuring impact that is both broader and timelier than citations. We present preliminary findings that automated Twitter accounts create a considerable amount of tweets to scientific papers and that they behave differently than common social bots, which has critical implications for the use of raw tweet counts in research evaluation and assessment. We discuss some definitions of Twitter cyborgs and bots in scholarly communication and propose differentiating between different levels of engagement from tweeting only bibliographic information to discussing or commenting on the content of a paper.

Direct to Full Text (9 pages; PDF)
See Also: Additional Papers Available on arXiv by Lead Author Stefanie Haustein
Note: Several papers available here were co-authored by the same group as the paper linked to above.

Filed under: Journal Articles, News, Open Access, Reports