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Related Experiment Video

Updated: Jul 15, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Majority model on a network with communities.

R Lambiotte¹, M Ausloos, J A Hołyst

¹Université de Liège, Sart-Tilman, B-4000 Liège, Belgium.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|May 16, 2007

Summary

In social networks, two communities can either reach consensus or opposite opinions based on their interconnectivity. The study reveals a critical transition point influencing this outcome and highlights the role of the interface between groups.

Related Experiment Videos

Last Updated: Jul 15, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Area of Science:

Computational Social Science
Network Science
Statistical Physics

Background:

Social networks often exhibit community structures, where groups of individuals interact more frequently within than between groups.
Understanding opinion dynamics within these segregated structures is crucial for predicting social behavior and information diffusion.

Purpose of the Study:

To investigate opinion dynamics in a model social network composed of two coupled, fully connected communities.
To identify the conditions under which consensus or divergent opinions emerge between these communities.

Main Methods:

Utilized the majority model on a network topology of two interconnected fully connected subnetworks.
Analyzed the system's behavior by varying the interconnectivity parameter between the two communities.

Main Results:

Identified a critical transition point in the interconnectivity parameter.
Above this threshold, only symmetric solutions (consensus) were observed, indicating agreement between communities.
Below this threshold, asymmetric states (opposite opinions) were attained, demonstrating divergence.

Conclusions:

The interconnectivity strength critically determines whether coupled social network communities reach consensus or opposing views.
The interface between subnetworks plays a significant role in mediating opinion dynamics and the emergent state.