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arXiv Open Access 2023

Social Bots: Detection and Challenges

Kai-Cheng Yang Onur Varol Alexander C. Nwala Mohsen Sayyadiharikandeh Emilio Ferrara +2 lainnya
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Abstrak

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.

Topik & Kata Kunci

cs.SI

Penulis (7)

K

Kai-Cheng Yang

O

Onur Varol

A

Alexander C. Nwala

M

Mohsen Sayyadiharikandeh

E

Emilio Ferrara

A

Alessandro Flammini

F

Filippo Menczer

Format Sitasi

APA MLA BibTeX
Yang, K., Varol, O., Nwala, A.C., Sayyadiharikandeh, M., Ferrara, E., Flammini, A. et al. (2023). Social Bots: Detection and Challenges. https://arxiv.org/abs/2312.17423

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Sumber Database
arXiv
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Open Access ✓