The role of bot squads in the political propaganda on Twitter

Guido Caldarelli,Fabio Saracco,Marinella Petrocchi,Rocco De Nicola,Fabio Del Vigna

doi:10.1038/s42005-020-0340-4

Abstract

Nowadays, Social Media are a privileged channel for news spreading, information exchange, and fact checking. Unexpectedly for many users, automated accounts, known as social bots, contribute more and more to this process of information diffusion. Using Twitter as a benchmark, we consider the traffic exchanged, over one month of observation, on the migration flux from Northern Africa to Italy. We measure the significant traffic of tweets only, by implementing an entropy-based null model that discounts the activity of users and the virality of tweets. Results show that social bots play a central role in the exchange of significant content. Indeed, not only the strongest hubs have a number of bots among their followers higher than expected, but furthermore a group of them, that can be assigned to the same political tendency, share a common set of bots as followers. The retweeting activity of such automated accounts amplifies the hubs’ messages.

Highlights

Nowadays, Social Media are a privileged channel for news spreading, information exchange, and fact checking
Once we have cleaned the system from the random noise via the application of the null-model, we study the effects of social bots in retweeting a significant amount of messages on Twitter
Online media are not trusted as their offline counterparts: in a survey conducted in autumn 2017, 59% of respondents said they trusted radio content, while only 20% said they trusted information available on online social networks

Summary

Introduction

Social Media are a privileged channel for news spreading, information exchange, and fact checking. Helped by the simple activity consisting of creating a text of 140 ( 280) characters, on Twitter we assist to the proliferation of social accounts governed—completely or in part—by pieces of software that automatically create, share, and like contents on the platform. Such software, known as social bots— or bots—can be programmed to automatically post information about news of any kind and even to provide help during emergencies. The supervised approach proposed by Cresci et al in ref. 14 tested a series of classification rules proposed by bloggers, and features sets by Academia, on a reference dataset of genuine and fake accounts, leading to the implementation of a classifier, which significantly reduces the cost for data gathering

Methods

Results

Conclusion