Control Strategies for Recommendation Systems in Social Networks

TL;DR

This paper introduces control strategies for recommendation systems in social networks, using a novel model that integrates opinion dynamics to optimize user engagement and influence opinion formation.

Contribution

It develops and formalizes both model-free and model-based control approaches within an extended Friedkin-Johnsen model for social opinion dynamics.

Findings

Control strategies effectively maximize user engagement

Proposed methods influence opinion formation processes

Numerical simulations validate the approaches

Abstract

A closed-loop control model to analyze the impact of recommendation systems on opinion dynamics within social networks is introduced. The core contribution is the development and formalization of model-free and model-based approaches to recommendation system design, integrating the dynamics of social interactions within networks via an extension of the Friedkin-Johnsen (FJ) model. Comparative analysis and numerical simulations demonstrate the effectiveness of the proposed control strategies in maximizing user engagement and their potential for influencing opinion formation processes.