Independence of Sources in Social Networks

TL;DR

This paper introduces a belief function-based method to estimate cognitive independence between users in social networks, demonstrated through experiments on Twitter data, aiding community detection and influencer identification.

Contribution

It presents a novel approach using belief functions to quantify user independence in social networks, enhancing analysis of social structures.

Findings

Effective estimation of user independence on Twitter

Improved community detection potential

Quantitative measure for influence analysis

Abstract

Online social networks are more and more studied. The links between users of a social network are important and have to be well qualified in order to detect communities and find influencers for example. In this paper, we present an approach based on the theory of belief functions to estimate the degrees of cognitive independence between users in a social network. We experiment the proposed method on a large amount of data gathered from the Twitter social network.