Social Media Influence Operations

• URL: http://arxiv.org/abs/2309.03670v1
• Date: Thu, 7 Sep 2023 12:18:07 GMT
• Title: Social Media Influence Operations
• Authors: Raphael Meier
• Abstract summary: This article reviews developments at the intersection of Large Language Models (LLMs) and influence operations. LLMs are able to generate targeted and persuasive text which is for the most part indistinguishable from human-written content. mitigation measures for the near future are highlighted.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Social media platforms enable largely unrestricted many-to-many communication. In times of crisis, they offer a space for collective sense-making and gave 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) in order to shape public opinion and interfere in decision-making processes. CeSIOs rely on the employment of 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 are able to 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.

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