AI for Human and Misinformation Interactions

doi:10.1017/9781009587877.008

7 - AI for Human and Misinformation Interactions

A Case of Social Media

Published online by Cambridge University Press: 19 September 2025

Nannan Huang,

Xiuzhen Zhang and

Jia Tina Du

Edited by

Dan Wu and

Shaobo Liang

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Dan Wu: Affiliation:
Wuhan University, China
Shaobo Liang: Affiliation:
Wuhan University, China

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Summary

Misinformation on social media is a recognized threat to societies. Research has shown that social media users play an important role in the spread of misinformation. It is crucial to understand how misinformation affects user online interaction behavior and the factors that contribute to it. In this study, we employ an AI deep learning model to analyze emotions in user online social media conversations about misinformation during the COVID-19 pandemic. We further apply the Stimuli–Organism–Response framework to examine the relationship between the presence of misinformation, emotions, and social bonding behavior. Our findings highlight the usefulness of AI deep learning models to analyze emotions in social media posts and enhance the understanding of online social bonding behavior around health-related misinformation.

Keywords

Misinformation Social Media Deep Learning Social Bonding Online Behavior Artificial Intelligence

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Type: Chapter
Information: Human-AI Interaction and Collaboration , pp. 153 - 174
DOI: https://doi.org/10.1017/9781009587877.008 [Opens in a new window]
Publisher: Cambridge University Press
Print publication year: 2025

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