Interplay between Emotional Dynamics and Network Structure on the Social Media Vent

2026-09-25

AI Summary

This study addresses the poorly understood interplay between emotional contagion and network structure on social media. Leveraging large-scale data from the Vent platform, this work integrates affective dynamics modeling with network topology analysis to examine how the emotional composition of users’ pre-posting timelines shapes their subsequent emotion labels, while revealing the heterogeneity of this effect across different network positions. The findings identify a cross-category “emotional priming” effect and demonstrate that users exhibiting high emotional alignment display significant spatial clustering within the network. By confirming that emotional expression is jointly driven by short-term contextual cues and network topology, this research offers a novel computational perspective for understanding online emotional propagation.

Abstract

The sharing and contagion of emotions on social media influence online interactions and users' psychological states. This study analyzes emotional dynamics on Vent, an emotion-sharing social media platform where users explicitly assign emotional labels to their own posts. Using a large-scale dataset, we examine how emotions in users' pre-posting timelines are associated with their subsequent emotional labels and how such associations vary across users. Our analysis reveals three key findings. First, users' subsequent emotional labels are associated with the emotional composition of their pre-posting timelines, with same-category emotions being overrepresented before posts in all analyzed categories. Second, several cross-category associations are observed; for example, Surprise was overrepresented before Fear posts; Affection and Happiness were overrepresented before Anger posts; and Affection was overrepresented before Sadness posts. Third, users differ in their degree of alignment with timeline emotional fluctuations, and highly aligned users tend to be located close to one another in the network. These findings provide large-scale observational evidence that emotional expression on Vent is associated with both short-term timeline context and network structure.

Problem

• emotional dynamics
• social media
• network structure
• emotion contagion
• Vent platform

Innovation

• Emotional Dynamics
• Network Structure
• Social Media
• Cross-category Associations
• Large-scale Observational Analysis