The evolution of online ideological communities

Area of Science:

• Social Sciences
• Computer Science
• Information Science

Background:

• Online communities facilitate knowledge exchange and social support.
• Understanding user behavior is crucial for marketing, security, and community management.
• Identifying user roles and their evolution is key to understanding community dynamics.

Purpose of the Study:

• To identify and categorize user roles within online ideological communities.
• To analyze user role changes and progression pathways over time.
• To explore the relationship between user roles and community health.

Main Methods:

• K-MEANS cluster analysis of behavioral meta-data to identify user roles.
• Mapping identified roles against the Reader-to-Leader Framework (RtLF).
• Longitudinal study of user role transitions over a two-year period.

Main Results:

• Seven distinct user roles were identified across two online ideological communities.
• Both communities aligned with the RtLF, with most users as contributors, followed by collaborators, and few leaders.
• User roles demonstrated stability over time despite high user churn, with a predictive model of role transitions developed.

Conclusions:

• A novel approach using meta-data effectively identifies diverse user roles and leadership potential.
• User role stability suggests predictable community structures, valuable for predicting future behavior.
• Findings have implications for community managers and security contexts, enabling proactive analysis of online behaviors.