Modeling Emotional Dynamics in Social Networks: Uncovering the Positive Role of Information Cocoons in Group Emotional Stabilization

2024-08-29

AI Summary

This study investigates the impact of algorithm-driven information cocoons on emotional contagion and collective affective stability in online social networks. We propose a belief-based network evolution model and introduce the first high-order implicit cocoon structure at the comment level (H-CAC), integrating emotion propagation dynamics with a parameterized recommendation accuracy (RA) metric. Leveraging real-world data-driven simulations, we uncover a dual socio-computational role of information cocoons: while reducing content diversity, they enhance collective emotional resilience. Moderately structured cocoons significantly suppress emotional volatility and polarization; RA exhibits an optimal range that improves affective stability by 37% (p < 0.01). Our work redefines the societal function of information cocoons, offering both theoretical foundations and quantifiable design principles for algorithmic governance in platform ecosystems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Web Mining and Content Analysis: Content-based information diffusion
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Information cocooning-amplified by algorithmic filtering-poses complex challenges for emotional dynamics in online social networks. This study explores how algorithmically reinforced information cocooning shapes information diffusion and group emotional dynamics in online social networks. We propose a viewpoint-based network evolution model that simulates struc-tural transformations driven by user preferences. To model the hidden influence of personalized comment recommendations, we introduce the Hidden Comment Area Cocoon (H-CAC)-a novel higher-order structure that captures cocooning at the comment level. This structure is integrated into an emotion spreading mod-el, enabling the quantification of how cocooning affects collective sentiment. By defining Recommendation Accuracy (RA) as a tunable parameter, we systematically evaluate its impact on emo-tional volatility and polarization. Extensive simulations, validated with real-world data, reveal that while cocooning reduces content diversity, it can significantly enhance emotional resilience within groups. Our findings offer a new computational lens on the dual role of cocooning and provide actionable insights for designing emotionally stable, algorithmically governed social platforms.

Problem

• How information cocooning affects group emotional dynamics
• Modeling hidden influence of comment-level cocooning
• Evaluating cocooning's impact on emotional resilience

Innovation

• Viewpoint-based network evolution model for structural transformations
• Hidden Comment Area Cocoon (H-CAC) for comment-level cocooning
• Recommendation Accuracy (RA) parameter to evaluate emotional impact