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Email services use spam filtering algorithms (SFAs) to filter emails that areunwanted by the user. However, at times, the emails perceived by an SFA asunwanted may be important to the user. Such incorrect decisions can havesignificant implications if SFAs treat emails of user interest as spam on alarge scale. This is particularly important during national elections. To studywhether the SFAs of popular email services have any biases in treating thecampaign emails, we conducted a large-scale study of the campaign emails of theUS elections 2020 by subscribing to a large number of Presidential, Senate, andHouse candidates using over a hundred email accounts on Gmail, Outlook, andYahoo. We analyzed the biases in the SFAs towards the left and the rightcandidates and further studied the impact of the interactions (such as readingor marking emails as spam) of email recipients on these biases. We observedthat the SFAs of different email services indeed exhibit biases towardsdifferent political affiliations. We present this and several other importantobservations in this paper.

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