A political radicalization framework based on Moral Foundations Theory

TL;DR

This paper introduces a novel framework based on Moral Foundations Theory to measure online community radicalization by analyzing interaction behaviors and network structures, revealing increased isolation and extremism in radicalized groups.

Contribution

It presents a data-driven method linking social network structure to moral foundations, enabling the detection of radicalized communities through behavioral and structural features.

Findings

Radicalized communities show increased isolation and domination.

Individuals share more extreme content than they publish.

Extreme views receive more likes on social media.

Abstract

Moral Foundations Theory proposes that individuals with conflicting political views base their behavior on different principles chosen from a small group of universal moral foundations. This study proposes using a set of widely accepted moral foundations (Fairness, Ingroup loyalty, Authority, and Purity) as proxies to determine the degree of radicalization of online communities. The fifth principle, Care, is generally surpassed by others, which are higher in the radicalized groups' moral hierarchy. Moreover, the presented data-driven methodological framework proposes an alternative way to measure whether a community complies with some moral principle or foundation: not evaluating its speech, but its behavior through interactions of its individuals, establishing a bridge between structural features of the interaction network and the intensity of communities' radicalization regarding the considered moral foundations. Two foundations may be assessed using the network's structural characteristics: Ingroup loyalty measured by group-level modularity, and Authority evaluated using group domination for detecting potential hierarchical substructures within the network. By analyzing the set of Pareto-optimal groups regarding a multidimensional moral relevance scale, the most radicalized communities are identified among those considered extreme in some of their attitudes or views. The application of the proposed framework is illustrated using real-world datasets. The radicalized communities' behavior exhibits increasing isolation, and its authorities and leaders show growing domination over their audience. There were also detected differences between users' behavior and speech, showing that individuals tend to share more 'extreme' ingroup content than that they publish: extreme views get more likes on social media.