Going Micro to Go Negative

Targeting Toxicity using Facebook and Instagram Ads

Authors

  • Fabio Votta University of Amsterdam
  • Arman Noroozian University of Amsterdam
  • Tom Dobber University of Amsterdam
  • Natali Helberger University of Amsterdam
  • Claes de Vreese University of Amsterdam

Keywords:

political communication, microtargeting, negative campaigning, toxicity, ad library

Abstract

Spreading uncivil negative campaign messages is a “high-risk, high reward” campaign strategy since certain voters are more likely to be swayed by negative messaging whereas other voters are more inclined to feel sympathy with the attacked. Due to its risks, campaigns may attempt to outsource their uncivil ads to outside groups thus distancing themselves from the negativity and potentially avoiding any backlash. But at a time when advertising platforms boast of their ability to deliver ads to highly targeted audiences, uncivil negative ads could also be optimized to narrowly target citizens to which they are more likely to appeal. To study whether such optimizations are occurring, we retrieve all online advertisements that were placed on Facebook platforms (incl. Instagram) in the seven months prior to the US 2020 election. We perform multilevel ordinal regressions and find that ads from official political campaigns are more likely to be toxic when targeted at a narrower audience, whereas “dark money” outside groups (like super PACs and non-profits) are more likely to target broad audiences with their toxicity. In addition, we find that ads from outside groups are more likely to be toxic. We discuss the findings in light of this evidence and reflect upon future research regarding microtargeting negative messages on online platforms such as Facebook and Instagram.

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Published

2023-02-06

How to Cite

Votta, F., Noroozian, A., Dobber, T., Helberger, N., & de Vreese, C. (2023). Going Micro to Go Negative: Targeting Toxicity using Facebook and Instagram Ads. Computational Communication Research, 5(1), 1–50. Retrieved from https://computationalcommunication.org/ccr/article/view/124

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Section

Articles