2026-09-15T23:22:08Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1498722025-04-30T20:38:54Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134486

00925njm 22002777a 4500 dc Shoeibi, Niloufar author Martín Mateos, Alberto author Rivas Camacho, Alberto author Corchado Rodríguez, Juan Manuel author Martin Mateos, Alberto author 2022 [EN] Due to the advancement of technology, and the promotion of smart- phones, using social media got more and more popular. Nowadays, it has become an undeniable part of people’s lives. So, they will create a flow of information by the content they share every single moment. Analyzing this information helps us to have a better understanding of users, their needs, their tendencies and classify them into different groups based on their behavior. These behaviors are various and due to some extracted features, it is possible to categorize the users into different categories. In this paper, we are going to focus on Twitter users and the AusOpen Tennis championship event as a case study. We define the attributions describing each class and then extract data and identify features that are more correlated to each type of user and then label user type based on the reasoning model. The results contain 4 groups of users; Verified accounts, Influencers, Regular profiles, and Fake profiles. Shoeibi, N., et al. (2022). A Feature Based Approach on Behavior Analysis of the Users on Twitter: A Case Study of AusOpen Tennis Championship. Advances in Intelligent Systems and Computing, vol 1237. Springer, Cham. 978-3-030-53035-8 http://hdl.handle.net/10366/149872 10.1007/978-3-030-53036-5_31 Social media analytics Behavior analysis User behavior mining Feature extraction Twitter Verified Influencers Regular and fakes A feature based approach on behavior analysis of the users on twitter: A case study of AusOpen tennis championship