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Content-based features predict social media influence operations
2020
Science Advances
We study how easy it is to distinguish influence operations from organic social media activity by assessing the performance of a platform-agnostic machine learning approach. Our method uses public activity to detect content that is part of coordinated influence operations based on human-interpretable features derived solely from content. We test this method on publicly available Twitter data on Chinese, Russian, and Venezuelan troll activity targeting the United States, as well as the Reddit
doi:10.1126/sciadv.abb5824
pmid:32832674
pmcid:PMC7439640
fatcat:7qe2k42wqjgrnhi5fchzafa5oa