Who Are Controlled by The Same User? Multiple Identities Deception Detection via Social Interaction Activity (Student Abstract)

Authors

  • Jiacheng Li Chinese Academy of Sciences
  • Chunyuan Yuan Chinese Academy of Sciences
  • Wei Zhou Chinese Academy of Sciences
  • Jingli Wang China Government Securities Depository Trust & Clearing Co., Ltd
  • Songlin Hu Chinese Academy of Sciences

DOI:

https://doi.org/10.1609/aaai.v34i10.7199

Abstract

Social media has become a preferential place for sharing information. However, some users may create multiple accounts and manipulate them to deceive legitimate users. Most previous studies utilize verbal or behavior features based methods to solve this problem, but they are only designed for some particular platforms, leading to low universalness.

In this paper, to support multiple platforms, we construct interaction tree for each account based on their social interactions which is common characteristic of social platforms. Then we propose a new method to calculate the social interaction entropy of each account and detect the accounts which are controlled by the same user. Experimental results on two real-world datasets show that the method has robust superiority over state-of-the-art methods.

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Published

2020-04-03

How to Cite

Li, J., Yuan, C., Zhou, W., Wang, J., & Hu, S. (2020). Who Are Controlled by The Same User? Multiple Identities Deception Detection via Social Interaction Activity (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 34(10), 13853-13854. https://doi.org/10.1609/aaai.v34i10.7199

Issue

Section

Student Abstract Track