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Human and Algorithmic Contributions to Misinformation Online - Identifying the Culprit Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Detecting Malicious Social Bots: Story of a Never-Ending Clash

Author : Stefano Cresci

Published in: Disinformation in Open Online Media

Publisher: Springer International Publishing

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Abstract

Recently, studies on the characterization and detection of social bots were published at an impressive rate. By looking back at over ten years of research and experimentation on social bots detection, in this paper we aim at understanding past, present, and future research trends in this crucial field. In doing so, we discuss about one of the nastiest features of social bots – that is, their evolutionary nature. Then, we highlight the switch from supervised bot detection techniques – focusing on feature engineering and on the analysis of one account at a time – to unsupervised ones, where the focus is on proposing new detection algorithms and on the analysis of groups of accounts that behave in a coordinated and synchronized fashion. These unsupervised, group-analyses techniques currently represent the state-of-the-art in social bot detection. Going forward, we analyze the latest research trend in social bot detection in order to highlight a promising new development of this crucial field.

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previous chapter What Is Abusive Language?
next chapter The Markets of Manipulation: The Trading of Social Bots on Clearnet and Darknet Markets
Footnotes
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Metadata
Title
Detecting Malicious Social Bots: Story of a Never-Ending Clash
Author
Stefano Cresci
Copyright Year
2020
Book
Disinformation in Open Online Media

Print ISBN: 978-3-030-39626-8

Electronic ISBN: 978-3-030-39627-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-39627-5_7

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