EMINDS: Understanding User Behavior Progression for Mental Health Exploration on Social Media

TL;DR

EMINDS is a visual analytics system that automatically mines and visualizes user behavior stages on social media to understand mental health progression, aiding early intervention and long-term impact analysis.

Contribution

The paper introduces EMINDS, a novel system that automatically extracts behavior stages and visualizes their evolution and impact on mental health over time.

Findings

Effective in revealing behavior stage patterns affecting mental health

Facilitates understanding of long-term behavior impacts

Validated through case studies and expert feedback

Abstract

Mental health is an urgent societal issue, and social scientists are increasingly turning to online mental health communities (OMHCs) to analyze user behavior data for early intervention. However, existing sequence mining techniques fall short of the urgent need to explore the behavior progression of different groups (e.g., recovery or deterioration groups) and track the potential long-term impact of behaviors on mental health status. To address this issue, we introduce EMINDS, a visual analytics system built on a novel automatic mining pipeline that extracts distinct behavior stages and assesses the potential impact of frequent stage patterns on mental health status over time. The system includes a set of interactive visualizations that summarize the meaning of each behavior stage and the evolution of different stage patterns. We feature a pattern-centric Sankey diagram to reveal contextual information about the impact of stage patterns on mental health, helping experts understand the specific changes in sequences before and after a stage pattern. We evaluated the effectiveness and usability of EMINDS through two case studies and expert interviews, which examined the potential stage patterns impacting long-term mental health by analyzing user behaviors on Reddit.