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Title: Are we secure from bots? Investigating vulnerabilities of botometer
Authors: Torusdağ, Buğra M.
Kutlu, Mücahid
Selçuk, Ali Aydın
Keywords: botometer
machine learning
social cyber security
social media
Twitter Bot Accounts
Issue Date: Sep-2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Torusdağ, M. B., Kutlu, M., and Selçuk, A. A. (2020, September). Are We Secure from Bots? Investigating Vulnerabilities of Botometer. In 2020 5th International Conference on Computer Science and Engineering (UBMK) (pp. 343-348). IEEE.
Abstract: Social media platforms such as Twitter provide an incredibly efficient way to communicate with people. While these platforms have many benefits, they can also be used for deceiving people, spreading misinformation, manipulation, and harassment. Social bots are usually employed for these kind of activities to artificially increase the amount of a particular post. To mitigate the effects of social bots, many bot detection systems are developed. However, the evaluation of these methods are challenging due to lack limited available datasets and the variety of bots people might develop. In this work, we investigate vulnerabilities of state-of-the-art Botometer social bot detection system by creating our own bot scenarios instead of using public datasets. In our experiments, we show that Botometer is not able to detect our social bots, showing that we need more enhanced bot detection models and test collections to better evaluate systems' performances. © 2020 IEEE.
ISBN: 978-172817565-2
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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