Yang, Kai Cheng and Varol, Onur and Nwala, Alexander C. and Sayyadiharikandeh, Mohsen and Ferrara, Emilio and Flammini, Alessandro and Menczer, Filippo (2025) Social bots: detection and challenges. In: Yasseri, Taha, (ed.) Handbook of Computational Social Science. Edward Elgar Publishing, Cheltenham, UK, pp. 473-491. ISBN 9781802207293 (Print) 9781802207309 (Online)
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Official URL: https://dx.doi.org/10.4337/9781802207309.00049
Abstract
Although social media is a key source of data for computational social science, the ease with which it can be manipulated by malicious actors threatens the integrity of online information exchanges and their analysis. In this chapter, we focus on malicious social bots, a prominent vehicle for such manipulation. We start by discussing recent studies about the presence and actions of social bots in various online discussions, highlighting their real-world implications and the need for detection methods. Then we discuss the challenges of bot detection methods and use Botometer, a publicly available bot detection tool, as a case study to describe recent developments in this area. We close with a practical guide on how to handle social bots in social media research.
| Item Type: | Book Section / Chapter |
|---|---|
| Uncontrolled Keywords: | Astroturfing; Bot Detection; Information Spreading; Online Manipulation; Social Bots; Twitter |
| Divisions: | Faculty of Engineering and Natural Sciences |
| Depositing User: | Onur Varol |
| Date Deposited: | 10 Apr 2026 14:43 |
| Last Modified: | 10 Apr 2026 14:43 |
| URI: | https://research.sabanciuniv.edu/id/eprint/53809 |

