Analytical model of misinformation of a social network node

TL;DR

This paper develops an analytical model to quantify how cognitive, behavioral, and representational factors influence social network nodes' susceptibility to misinformation, aiming to improve methods for blocking propaganda and understanding information warfare.

Contribution

It introduces a novel iterative learning-based model to calculate misinformation levels at individual social network nodes, considering psychological and behavioral factors.

Findings

Model effectively quantifies misinformation susceptibility.

Highlights importance of psychological factors in misinformation spread.

Provides a basis for developing anti-propaganda strategies.

Abstract

This paper presents the research of the influence of cognitive, behavioral, representational factors on the susceptibility of the participants in social networks to misinformation, as well as on the activity of the nodes in this regard. The importance of this research consists of method of blocking the propaganda. This is very important because when people involuntarily acquire information some of them experience an undesired change in their social attitude. Such phenomena typically lead towards the information warfare. A model was developed during this research for calculating the level of misinformation of the social network participant (network node) based on the model of iterative learning process.