mlsanityData to 14 Oct 2026

Social Bots: Detection and Challenges

arXiv 2312.17423 ↗First posted 29 Dec 2023cs.SIcited by 3

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Abstract (arXiv)

While social media are a key source of data for computational social science, their ease of manipulation 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 to show 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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Dec 2023.

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Citing papers per year: 2024: 2; 2025: 0; 2026: 1.

3 papers.