LLM-Aided Social Media Influence Operations

Abstract

AbstractSocial media platforms enable largely unrestricted many-to-many communication. In times of crisis, they offer a space for collective sense-making and give rise to new social phenomena (e.g., open-source investigations). However, they also serve as a tool for threat actors to conduct Cyber-enabled Social Influence Operations (CeSIOs) to shape public opinion and interfere in decision-making processes. CeSIOs employ sock puppet accounts to engage authentic users in online communication, exert influence, and subvert online discourse. Large Language Models (LLMs) may further enhance the deceptive properties of sock puppet accounts. Recent LLMs can generate targeted and persuasive text, which is, for the most part, indistinguishable from human-written content—ideal features for covert influence. This article reviews recent developments at the intersection of LLMs and influence operations, summarizes LLMs’ salience, and explores the potential impact of LLM-instrumented sock puppet accounts for CeSIOs. Finally, mitigation measures for the near future are highlighted.