A Peek into the Political Biases in Email Spam Filtering Algorithms During US Election 2020

TL;DR

This study investigates political biases in email spam filtering algorithms during the 2020 US elections by analyzing campaign emails across major email providers, revealing biases towards different political affiliations.

Contribution

The paper provides a large-scale empirical analysis of political biases in spam filters of Gmail, Outlook, and Yahoo during a national election, highlighting their differential treatment of political emails.

Findings

SFAs exhibit biases towards different political affiliations.

Biases vary across email services like Gmail, Outlook, Yahoo.

Recipient interactions influence the biases of spam filters.

Abstract

Email services use spam filtering algorithms (SFAs) to filter emails that are unwanted by the user. However, at times, the emails perceived by an SFA as unwanted may be important to the user. Such incorrect decisions can have significant implications if SFAs treat emails of user interest as spam on a large scale. This is particularly important during national elections. To study whether the SFAs of popular email services have any biases in treating the campaign emails, we conducted a large-scale study of the campaign emails of the US elections 2020 by subscribing to a large number of Presidential, Senate, and House candidates using over a hundred email accounts on Gmail, Outlook, and Yahoo. We analyzed the biases in the SFAs towards the left and the right candidates and further studied the impact of the interactions (such as reading or marking emails as spam) of email recipients on these biases. We observed that the SFAs of different email services indeed exhibit biases towards different political affiliations. We present this and several other important observations in this paper.