Red Bots Do It Better: Comparative Analysis of Social Bot Partisan Behavior

TL;DR

This study analyzes social bot behavior during the 2018 US midterm elections on Twitter, revealing that conservative bots are more embedded and influential than liberal bots, with distinct strategies and ideological behaviors.

Contribution

The paper provides a detailed comparative analysis of political social bots, including their classification, strategies, and influence during a major election event.

Findings

Conservative bots are more embedded and influential than liberal bots.

Social bots can be accurately classified by political leaning.

Liberal bots exhibit more inflammatory behavior and less topic overlap.

Abstract

Recent research brought awareness of the issue of bots on social media and the significant risks of mass manipulation of public opinion in the context of political discussion. In this work, we leverage Twitter to study the discourse during the 2018 US midterm elections and analyze social bot activity and interactions with humans. We collected 2.6 million tweets for 42 days around the election day from nearly 1 million users. We use the collected tweets to answer three research questions: (i) Do social bots lean and behave according to a political ideology? (ii) Can we observe different strategies among liberal and conservative bots? (iii) How effective are bot strategies? We show that social bots can be accurately classified according to their political leaning and behave accordingly. Conservative bots share most of the topics of discussion with their human counterparts, while liberal bots show less overlap and a more inflammatory attitude. We studied bot interactions with humans and observed different strategies. Finally, we measured bots embeddedness in the social network and the effectiveness of their activities. Results show that conservative bots are more deeply embedded in the social network and more effective than liberal bots at exerting influence on humans.