What is it about?
Social bots (algorithms that control profiles) are very active on social networks, for example, spreading fake news, viruses, or several kinds of scams. This work combines different strategies to increase the performance of bot detection algorithms. In particular, the users' profiles are clustered and a classification model, using artificial intelligence, is created for each cluster. The proposed approached was tested considering users that tweet about COVID-19, and it overperformed the related approaches.
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Why is it important?
Detecting bots in social networks is very important to prevent their harmful actions. Allowing real users to act in a more carefree way on social networks and favoring democratic debates.
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This page is a summary of: Combining clustering and classification algorithms for automatic bot detection: a case study on posts about COVID-19, June 2021, ACM (Association for Computing Machinery),
DOI: 10.1145/3466933.3466970.
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