Abstract
A social networking phenomenon grew extremely through the last twenty years. The number of people on social media platforms are incrementing at a greater level of malicious use. This Social network attracts millions of users across the world and their interaction with social networking has affected their life. This kind of population has led to different problems, including the possibility of exposing incorrect information to their users through fake accounts which results in the spread of malicious content. This situation can result in a huge damage in the real world to society. In our research, an overview of the methods of Twitter fake accounts detection presented with discussing their effectiveness. The datasets which are commonly used by Twitter fake accounts detection approaches are highlighted and the most used attributes are categorized and identified. Also, in the end of this study we will present the related work and give the description of the proposed method with presenting the results’ analysis.
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Oumaima, L., Ouafae, B., Mariam, R., Abdelouahid, L. (2022). An Overview of Detecting Fake Accounts on Twitter Networks. In: Kacprzyk, J., Balas, V.E., Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2020). AI2SD 2020. Advances in Intelligent Systems and Computing, vol 1417. Springer, Cham. https://doi.org/10.1007/978-3-030-90633-7_97
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DOI: https://doi.org/10.1007/978-3-030-90633-7_97
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