Modeling and Analysis of Information Communities

TL;DR

This paper introduces a mathematical model to analyze how communities form and structure themselves in information-based social networks, highlighting their role in content sharing and utility maximization.

Contribution

It presents a novel formal model for studying community emergence and structure specifically in information networks, a topic with limited prior formal analysis.

Findings

Model captures key properties of information communities

Communities form to maximize content utility

Structural characteristics align with real-world observations

Abstract

Communities are an important feature of social networks. In fact, it seems that communities are necessary for a social network to be efficient. However, there exist very few formal studies of the actual role of communities in social networks, how they emerge, and how they are structured. The goal of this paper is to propose a mathematical model to study communities in social networks. For this, we consider a particular case of a social network, namely information networks. We assume that there is a population of agents who are interested in obtaining content. Agents differ in the type of content they are interested in. The goal of agents is to form communities in order to maximize their utility for obtaining and producing content. We use this model to characterize the structure of communities that emerge in this setting. While the proposed model is very simple, the obtained results suggest that it indeed is able to capture key properties of information communities.