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The challenge is even made more pressing by evidence of these actors on platforms beyond the extensively studied X (formerly Twitter), as well as the emergence of new platforms. We fill this gap by introducing a novel compression-based detection methodology, in addition to a new sparse method for network reconstruction that scales linearly under reasonable parameter choice. Being independent of the social media platform and the behavioral trace under study, our approach marks a departure from traditional methods that rely on multiple criteria or measures to assess user similarity. We evaluate our technique on multiple benchmark and real-world datasets, including widely known datasets related to political campaigns and emerging misinformation scenarios. 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