Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/9080
Title: Evaluation of social bot detection models
Authors: Torusdag, M. Bugra
Kutlu, Mucahid
Selcuk, Ali Aydin
Keywords: Twitter
Social Bot Detection
Evaluation
Reproducibility
Networks
Design
Issue Date: 2022
Publisher: Scientific And Technological Research Council Turkey
Abstract: Social bots are employed to automatically perform online social network activities; thereby, they can also be utilized in spreading misinformation and malware. Therefore, many researchers have focused on the automatic detection of social bots to reduce their negative impact on society. However, it is challenging to evaluate and compare existing studies due to difficulties and limitations in sharing datasets and models. In this study, we conduct a comparative study and evaluate four different bot detection systems in various settings using 20 different public datasets. We show that high-quality datasets covering various social bots are critical for a reliable evaluation of bot detection methods. In addition, our experiments suggest that Botometer is preferable to others in order to detect social bots.
URI: https://doi.org/10.55730/1300-0632.3848
https://search.trdizin.gov.tr/yayin/detay/533998
https://hdl.handle.net/20.500.11851/9080
ISSN: 1300-0632
1303-6203
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
TR Dizin İndeksli Yayınlar / TR Dizin Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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