Computer and Modernization ›› 2022, Vol. 0 ›› Issue (03): 1-6.

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Social Bots Detection Based on Generative Adversarial Networks

  

  1. (1. National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data (PSRPC), 
    China Academy of Electronics and Information Technology, Beijing 100041, China;

    2. School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China)
  • Online:2022-04-29 Published:2022-04-29

Abstract: Twitter is a social media with hundreds of millions of active users. Nearly 15% of bot accounts are controlled by automated programs. Some of these bot accounts are malicious account that spread malicious information. Although researchers have developed a large number of sophisticated bot account detection methods, they all require prior knowledge of bot accounts which are lack of generalization. In order to solve these problems, this paper proposes to use the discriminator from generative adversarial network for bot account detection. This makes it possible to obtain a good detection model with the examples of real accounts. Experiments on a popular dataset show that the AUC achieves 94% classification effect.

Key words: social bots, generative adversarial networks, bot account detection