Abstract
Recent years have witnessed the increasing abuse of coordinated accounts on multiple social media platforms. Such accounts are usually operated by misinformation campaigns to manipulate the public opinions on different platforms jointly. However, existing methods mainly focus on detecting such accounts by capturing the coordinated activities within a single platform. As a result, their performances are limited as they can not make use of the information from other platforms. In this work, we propose that capturing cross-platform coordinated activities can bring a significant boost to identifying the accounts operated by misinfromation campaigns. To leverage such information in a practical way, we design a novel Conditional Gaussian-distribution Basis to extract cross-platform correlation from Coordinated Activity Set, which can be easily acquired. Experimental results indicate that our methodology outperform baselines and its own variants that can not leverage cross-platform information.
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Notes
- 1.
The information here mean the posts on Reddit and tweets on Twitter.
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Acknowledgement
The work in this paper is supported by NSF Research Grant IIS-2226087. The views and conclusions in this paper are of the authors and should not be interpreted as representing the social policies of the funding agency, or U.S. Government. Yizhou Zhang is also partially supported by the Annenberg Fellowship of the University of Southern California. We are sincerely thankful to our anonymous reviewers for their feedback, comments and suggestions.
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Zhang, Y., Sharma, K., Liu, Y. (2023). Capturing Cross-Platform Interaction for Identifying Coordinated Accounts of Misinformation Campaigns. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13981. Springer, Cham. https://doi.org/10.1007/978-3-031-28238-6_61
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DOI: https://doi.org/10.1007/978-3-031-28238-6_61
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