Appeal and Scope of Misinformation Spread by AI Agents and Humans

TL;DR

This study quantifies the influence of misinformation spread by AI bots and humans on social networks, introducing new metrics to measure tweet appeal and scope, and analyzing COVID-19 vaccine discourse over time.

Contribution

It proposes novel metrics for assessing misinformation impact and provides a comprehensive analysis of misinformation dynamics involving humans and AI bots during COVID-19.

Findings

Human misinformation tweets had higher appeal and scope than bots.

Misinformation was more prevalent during early COVID-19 periods.

Human tweets peaked in impact during Vaccine Launch week.

Abstract

This work examines the influence of misinformation and the role of AI agents, called bots, on social network platforms. To quantify the impact of misinformation, it proposes two new metrics based on attributes of tweet engagement and user network position: Appeal, which measures the popularity of the tweet, and Scope, which measures the potential reach of the tweet. In addition, it analyzes 5.8 million misinformation tweets on the COVID-19 vaccine discourse over three time periods: Pre-Vaccine, Vaccine Launch, and Post-Vaccine. Results show that misinformation was more prevalent during the first two periods. Human-generated misinformation tweets tend to have higher appeal and scope compared to bot-generated ones. Tweedie regression analysis reveals that human-generated misinformation tweets were most concerning during Vaccine Launch week, whereas bot-generated misinformation reached its highest appeal and scope during the Pre-Vaccine period.