The Impact of Disinformation on a Controversial Debate on Social Media

TL;DR

This study analyzes how disinformation spreads on Twitter during the Italian immigration debate, highlighting the roles of untrustworthy users and social bots in disseminating unreliable content within community networks.

Contribution

It introduces an ntrustworthiness score to characterize user behavior and reveals the interaction between social bots and unreliable content in social media networks.

Findings

Untrustworthy users are unevenly distributed across communities.

Social bots inject malicious content mainly into limited clusters.

Bots target reliable content to expand their influence.

Abstract

In this work we study how pervasive is the presence of disinformation in the Italian debate around immigration on Twitter and the role of automated accounts in the diffusion of such content. By characterising the Twitter users with an \textit{Untrustworthiness} score, that tells us how frequently they engage with disinformation content, we are able to see that such bad information consumption habits are not equally distributed across the users; adopting a network analysis approach, we can identify communities characterised by a very high presence of users that frequently share content from unreliable news sources. Within this context, social bots tend to inject in the network more malicious content, that often remains confined in a limited number of clusters; instead, they target reliable content in order to diversify their reach. The evidence we gather suggests that, at least in this particular case study, there is a strong interplay between social bots and users engaging with unreliable content, influencing the diffusion of the latter across the network.