Social Media Influence Operations

TL;DR

This paper reviews how large language models can enhance social media influence operations by creating convincing sock puppet accounts, discusses potential impacts, and suggests mitigation strategies.

Contribution

It provides a comprehensive overview of recent developments linking LLMs to influence operations and explores mitigation approaches for future threats.

Findings

LLMs can generate highly persuasive and human-like content.

Sock puppet accounts powered by LLMs pose increased risks for misinformation.

Mitigation strategies are necessary to counteract LLM-enhanced influence operations.

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.