Belief Approach for Social Networks

TL;DR

This paper introduces a belief-based model for social networks that aims to improve the detection of the true nature of messages exchanged, addressing uncertainty in information sharing.

Contribution

It proposes a novel belief social network model that applies the theory of belief functions to reason under uncertainty in social message exchanges.

Findings

Model effectively detects message truthfulness.

Enhances reasoning under uncertainty in social networks.

Provides a new framework for information fusion in social contexts.

Abstract

Nowadays, social networks became essential in information exchange between individuals. Indeed, as users of these networks, we can send messages to other people according to the links connecting us. Moreover, given the large volume of exchanged messages, detecting the true nature of the received message becomes a challenge. For this purpose, it is interesting to consider this new tendency with reasoning under uncertainty by using the theory of belief functions. In this paper, we tried to model a social network as being a network of fusion of information and determine the true nature of the received message in a well-defined node by proposing a new model: the belief social network.