Study: Gmail filtering leans left, marked 77% of conservative emails as "spam" in 2020 Election

Apr 10th

A new study from North Carolina State University found Google's email service Gmail favored liberal candidates and suppressed conservative candidates in the 2020 election.

The study found Gmail's spam-filtering algorithm (SFA) sent 77.2% of right-wing candidate emails to the spam folder in the months leading up to the 2020 election.

The study titled "A Peek into the Political Biases in Email Spam Filtering Algorithms During US Election 2020" was conducted from July 1, 2020 to November 30, 2020 on Gmail, Outlook, and Yahoo.

The researchers said Gmail's SFA "leaned towards the left" and "retained the majority of left-wing candidate emails in inbox," while Outlook and Yahoo "leaned towards the right."

A Google spokesperson said "political affiliation has absolutely no bearing on mail classifications in Gmail" and that "classifications in Gmail automatically adjust to match Gmail users' preferences and actions."

"The spam filtering algorithms (SFAs) in the widely-used email services of today such as Gmail, Outlook, and Yahoo do not provide any transparency on their internal workings. Given the lack of this transparency, an important question to study is whether these SFAs hold any biases towards certain political affiliations," the researchers wrote. "This question is motivated by the growing body of evidence suggesting that the biases in online algorithms can influence undecided voters."

The study also found "that the percentage of emails marked by Gmail as spam from the right-wing candidates grew steadily as the election date approached while the percentage of emails marked as spam from the left-wing candidates remained about the same."

"We conclude by noting that fairness of spam filtering algorithm is an important problem that needs dedicated attention from email service providers, particularly due to the enormous influence that electronic communication has in our lives today and will have going forward," the researchers wrote. "Therefore, there is an imminent need to develop techniques that reduce the biases of SFAs while simultaneously ensuring that the users do not receive unwanted emails."


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