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Published Online: 1 December 2017

Social Bots: Human-Like by Means of Human Control?

Publication: Big Data
Volume 5, Issue Number 4

Abstract

Social bots are currently regarded an influential but also somewhat mysterious factor in public discourse and opinion making. They are considered to be capable of massively distributing propaganda in social and online media, and their application is even suspected to be partly responsible for recent election results. Astonishingly, the term social bot is not well defined and different scientific disciplines use divergent definitions. This work starts with a balanced definition attempt, before providing an overview of how social bots actually work (taking the example of Twitter) and what their current technical limitations are. Despite recent research progress in Deep Learning and Big Data, there are many activities bots cannot handle well. We then discuss how bot capabilities can be extended and controlled by integrating humans into the process and reason that this is currently the most promising way to realize meaningful interactions with other humans. This finally leads to the conclusion that hybridization is a challenge for current detection mechanisms and has to be handled with more sophisticated approaches to identify political propaganda distributed with social bots.

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References

Cite this article as: Grimme C, Preuss M, Adam L, Trautmann H (2017) Social bots: human-like by means of human control? Big Data 5:4, 279–293, DOI: 10.1089/big.2017.0044.

Information & Authors

Information

Published In

cover image Big Data
Big Data
Volume 5Issue Number 4December 2017
Pages: 279 - 293
PubMed: 29235915

History

Published in print: December 2017
Published online: 1 December 2017

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Christian Grimme* [email protected]
Department of Information Systems, University of Münster, Münster, Germany.
Mike Preuss
Department of Information Systems, University of Münster, Münster, Germany.
Lena Adam
Department of Information Systems, University of Münster, Münster, Germany.
Heike Trautmann
Department of Information Systems, University of Münster, Münster, Germany.

Notes

*
Address correspondence to: Christian Grimme, Department of Information Systems, University of Münster, Leonardo-Campus 3, Münster 48419, Germany, E-mail: [email protected]

Author Disclosure Statement

No competing financial interests exist.

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