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The Elon Musk Paradox: Quantifying the Presence and Impact of Twitter Bots on Altmetrics with Focus in Social Sciences

Name: The Elon Musk Paradox: Quantifying the Presence and Impact of Twitter Bots on Altmetrics with Focus in Social Sciences
Keywords: X, Altmetrics, bots, Twitter, Social Sciences

descriptionPublicationkeyboard_double_arrow_right Presentation , Other literature type , Article 27 Sep 2023 English Publisher:Zenodo

Authors: Arroyo-Machado, Wenceslao; Herrera-Viedma, Enrique; Torres-Salinas, Daniel;

doi: 10.5281/zenodo.8385551 , 10.5281/zenodo.8385550

The Elon Musk Paradox: Quantifying the Presence and Impact of Twitter Bots on Altmetrics with Focus in Social Sciences

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Abstract

With the rise of Twitter bots in social and political spheres, their implications in scientific communication and altmetrics have become a concern. However, there are no large-scale studies that identify the population of bots and their impact on altmetrics. This quantitative study aims to analyse the presence and impact of Twitter bots in the dissemination of Social Science papers on Twitter and to explore the specific case of Information Science & Library Science (ISLS) as a case study. The overall presence of bots discussing Social Science papers has been found to account for 3.61% of users and 3.85% of tweets. However, this presence and impact is uneven across disciplines, highlighting Criminology & Penology with 12.4% of the mentions made by bots. In the specific case of ISLS, it has been determined by Kendall's correlation that mentions of bots have no impact on altmetrics.

Full paper available at: https://dapp.orvium.io/deposits/644235015db3c5af25159230/view

Related Organizations

University of Granada
Spain

Keywords

X, Altmetrics, bots, Twitter, Social Sciences

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

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