Influence of the majority group on individual judgments in online spontaneous conversations

2025-09-25

AI Summary

This study investigates how majority-group exposure influences individual judgment formation and expression in anonymous, spontaneous online dialogues. Drawing on social conformity and counter-conformity theories, it examines everyday dilemma discussions on social media, quantifying individual judgments via digital trace data. Using Bayesian regression, it models judgment shifts before and after majority-group exposure, while linguistic analysis tests motivated expression. Results reveal a systematic “affect-consistent–position-divergent” counter-conformity pattern: individuals retain the majority’s affective valence yet deliberately deviate from its stance; following opinion disclosure, they significantly increase persuasive language use. These findings demonstrate that anonymity reconfigures traditional social influence pathways, highlighting a novel dual mechanism—emotional anchoring coupled with strategic self-presentation. The study advances theoretical understanding of group influence in digital contexts and establishes a methodological paradigm integrating computational trace analysis, probabilistic modeling, and discourse-based validation.

Technology Category

• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

This study investigates how the majority group influences individual judgment formation and expression in anonymous, spontaneous online conversations. Drawing on theories of social conformity and anti-conformity, we analyze everyday dilemmas discussed on social media. First, using digital traces to operationalize judgments, we measure the conversations' disagreement and apply Bayesian regression to capture shifts of judgments formation before and after the group's exposure. Then we analyze changes in judgment expression with a linguistic analysis of the motivations associated with each judgment. Results show systematic anti-conformity behaviors: individuals preserve the majority's positive or negative orientation of judgments but diverge from its stance, with persuasive language increasing post-disclosure. Our findings highlight how online environments reshape social influence compared to offline contexts.

Problem

• Investigates majority group influence on individual judgment formation
• Analyzes judgment shifts in anonymous online spontaneous conversations
• Examines how online environments reshape social influence dynamics

Innovation

• Bayesian regression measures judgment formation shifts
• Linguistic analysis tracks judgment expression changes
• Digital traces operationalize judgments in conversations