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.
翻译:电子邮件服务使用垃圾邮件过滤算法(SFAs)过滤用户不需要的电子邮件。然而,有时,SFA认为不需要的电子邮件可能对用户很重要。如果SFA将用户感兴趣的电子邮件作为大规模垃圾邮件处理,这种不正确的决定可能会产生重大影响。这在全国选举中尤其重要。为了研究大众电子邮件服务SFA在处理竞选邮件时是否有任何偏向,我们通过在Gmail、Outlook和Yahoo上订阅大量总统、参议院和众议院候选人,对2020年选举的竞选电子邮件进行了大规模研究。我们分析了SFA对左方和右方候选人的偏见,并进一步研究了电子邮件接收者互动的影响(如阅读或标记电子邮件为垃圾邮件)。我们发现,不同电子邮件服务的SFA对不同的政治联系确实表现出偏见。我们在这个文件中介绍了这一点和其他一些重要观点。