Toxic Content and User Engagement on Social Media: Evidence from a Field Experiment

83 Pages Posted: 29 Dec 2022 Last revised: 21 Jan 2023

See all articles by George Beknazar-Yuzbashev

George Beknazar-Yuzbashev

Columbia University

Rafael Jiménez Durán

Bocconi University - Department of Economics; University of Chicago

Jesse McCrosky

Mozilla Foundation

Mateusz Stalinski

University of Chicago

Date Written: November 1, 2022

Abstract

As much as forty percent of social media users have been harassed online, but there is scarce causal evidence of how toxic content impacts user engagement and whether it is contagious. In a pre-registered field experiment, we recruited participants to install a browser extension, and randomly assigned them to either a treatment group where the extension automatically hides toxic text content on Facebook, Twitter, and YouTube, or to a control group without hiding. As the first stage, 6.6% of the content displayed to users was classified as toxic by the extension relying on state-of-the-art toxicity detection tools, and duly hidden in the treatment group during a six-week long period. Lowering exposure to toxicity reduced content consumption on Facebook by 23% relative to the mean - beyond the mechanical effect of our intervention. We also report a 9.2% drop in ad consumption on Twitter (relative to the mean), where this metric is available. Additionally, the intervention reduced the average toxicity of content posted by users on Facebook and Twitter, evidence of toxicity being contagious. Taken together, our results suggest a trade-off faced by platforms: they can curb users’ toxicity at the expense of their content consumption.

Keywords: toxic content, hate speech, moderation, social media, user engagement, field experiment

JEL Classification: C93, D12, D83, D90, I31, L82, L86, M37, Z13

Suggested Citation

Beknazar-Yuzbashev, George and Jiménez Durán, Rafael and McCrosky, Jesse and Stalinski, Mateusz, Toxic Content and User Engagement on Social Media: Evidence from a Field Experiment (November 1, 2022). Available at SSRN: https://ssrn.com/abstract=4307346 or http://dx.doi.org/10.2139/ssrn.4307346

George Beknazar-Yuzbashev (Contact Author)

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Rafael Jiménez Durán

Bocconi University - Department of Economics ( email )

Via Gobbi 5
Milan, 20136
Italy

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Jesse McCrosky

Mozilla Foundation ( email )

Mateusz Stalinski

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

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