The Social System Identification Problem

TL;DR

This paper introduces a method to model and identify influence dynamics in social networks by sampling opinions and using stubborn agents as known inputs, enabling inference of social influence and trust links.

Contribution

It presents a novel model and regression-based solution for probing social networks and estimating influence and trust relationships from opinion data.

Findings

Effective inference of social influence links

Mapping opinions to system equations

Estimating trust levels in social links

Abstract

The focus of this paper is modeling what we call a Social Radar, i.e. a method to estimate the relative influence between social agents, by sampling their opinions and as they evolve, after injecting in the network stubborn agents. The stubborn agents opinion is not influenced by the peers they seek to sway, and their opinion bias is the known input to the social network system. The novelty is in the model presented to probe a social network and the solution of the associated regression problem. The model allows to map the observed opinion onto system equations that can be used to infer the social graph and the amount of trust that characterizes the links.