ChestyBot: Detecting and Disrupting Chinese Communist Party Influence Stratagems

--Foreign information operations conducted by Russian and Chinese actors exploit the United States' permissive information environment. These campaigns threaten democratic institutions and the broader Westphalian model. Y et, existing detection and mitigation strategies often fail to identify active information campaigns in real time. This paper introduces ChestyBot, a pragmatics-based language model that detects unlabeled foreign malign influence tweets with up to 98.34% accuracy. The model supports a novel framework to disrupt foreign influence operations in their formative stages. Foreign influence campaigns--particularly those attributed to Russia during the 2016 U.S. Presidential Election--demonstrated how state-sponsored social media operations can destabilize democratic societies [1]. During that campaign, social media posts emanating from one state - Russia - probably represented an intentional effort to influence the internal affairs of another country - the United States. Though these efforts may not have changed election outcomes, they nonetheless constitute an erosion of the Westphalian state model itself [2]. In recent years, China has attempted to use social media to influence foreign perceptions of internal matters such as the Beijing 2022 Winter Olympics, the origins of COVID-19, and the human rights abuses in Xinjiang [3]. Despite these initiatives, China has (as far as we can tell at the time of this writing) not performed a successful large-scale disinformation campaign directed against U.S. internal interests.