Community Fact-Checks Trigger Moral Outrage in Replies to Misleading Posts on Social Media

2024-09-13

arXiv.org

AI Summary

This study investigates how community-based fact-checking—exemplified by X’s Community Notes—shapes users’ emotional responses to misleading posts. Leveraging a panel dataset of 2.22 million replies, we employ a quasi-experimental design combined with natural language processing to quantify shifts in negative and moral emotions. Results reveal, for the first time, that community fact-checking significantly amplifies moral outrage (+16.0%), while also increasing overall negative affect (+7.3%), anger (+13.2%), and disgust (+4.7%). These findings indicate that users interpret misinformation dissemination as a violation of social norms and respond with morally charged affect. The study provides critical behavioral evidence for designing community-driven correction mechanisms, demonstrating that collective fact-checking functions not only as an informational intervention but also as an affective mobilization tool—eliciting normative condemnation and reinforcing shared epistemic standards.

Technology Category

• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Application Domains: Misinformation & Fake News
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Responsible Web: Mitigating misinformation and disinformation
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Displaying community fact-checks is a promising approach to reduce engagement with misinformation on social media. However, how users respond to misleading content emotionally after community fact-checks are displayed on posts is unclear. Here, we employ quasi-experimental methods to causally analyze changes in sentiments and (moral) emotions in replies to misleading posts following the display of community fact-checks. Our evaluation is based on a large-scale panel dataset comprising N=2,225,260 replies across 1841 source posts from X's Community Notes platform. We find that informing users about falsehoods through community fact-checks significantly increases negativity (by 7.3%), anger (by 13.2%), disgust (by 4.7%), and moral outrage (by 16.0%) in the corresponding replies. These results indicate that users perceive spreading misinformation as a violation of social norms and that those who spread misinformation should expect negative reactions once their content is debunked. We derive important implications for the design of community-based fact-checking systems.

Problem

• Social Media
• Misinformation
• Emotional Response

Innovation

• Social Media
• Misinformation Detection
• User Emotional Response