Swinging in the States: Does disinformation on Twitter mirror the US presidential election system?

TL;DR

This study investigates how Twitter traffic related to the 2020 US presidential election reflects the electoral system, revealing that most disinformation and bot activity focus on swing states, highlighting the system's influence on online debates.

Contribution

The paper demonstrates that Twitter disinformation and bot activity are predominantly concentrated on swing states, linking electoral system features to online misinformation dynamics.

Findings

88% of Twitter traffic is associated with swing states

Non-trustworthy news links are more shared in swing-related traffic

Social bots mainly generate non-trustworthy tweets in swing states

Abstract

For more than a decade scholars have been investigating the disinformation flow on social media contextually to societal events, like, e.g., elections. In this paper, we analyze the Twitter traffic related to the US 2020 pre-election debate and ask whether it mirrors the electoral system. The U.S. electoral system provides that, regardless of the actual vote gap, the premier candidate who received more votes in one state `takes' that state. Criticisms of this system have pointed out that election campaigns can be more intense in particular key states to achieve victory, so-called {\it swing states}. Our intuition is that election debate may cause more traffic on Twitter-and probably be more plagued by misinformation-when associated with swing states. The results mostly confirm the intuition. About 88\% of the entire traffic can be associated with swing states, and links to non-trustworthy news are shared far more in swing-related traffic than the same type of news in safe-related traffic. Considering traffic origin instead, non-trustworthy tweets generated by automated accounts, so-called social bots, are mostly associated with swing states. Our work sheds light on the role an electoral system plays in the evolution of online debates, with, in the spotlight, disinformation and social bots.