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On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook

Published: 29 January 2019 Publication History

Abstract

Targeted advertising is meant to improve the efficiency of matching advertisers to their customers. However, targeted advertising can also be abused by malicious advertisers to efficiently reach people susceptible to false stories, stoke grievances, and incite social conflict. Since targeted ads are not seen by non-targeted and non-vulnerable people, malicious ads are likely to go unreported and their effects undetected. This work examines a specific case of malicious advertising, exploring the extent to which political ads1 from the Russian Intelligence Research Agency (IRA) run prior to 2016 U.S. elections exploited Facebook's targeted advertising infrastructure to efficiently target ads on divisive or polarizing topics (e.g., immigration, race-based policing) at vulnerable sub-populations. In particular, we do the following: (a) We conduct U.S. census-representative surveys to characterize how users with different political ideologies report, approve, and perceive truth in the content of the IRA ads. Our surveys show that many ads are "divisive": they elicit very different reactions from people belonging to different socially salient groups. (b) We characterize how these divisive ads are targeted to sub-populations that feel particularly aggrieved by the status quo. Our findings support existing calls for greater transparency of content and targeting of political ads. (c) We particularly focus on how the Facebook ad API facilitates such targeting. We show how the enormous amount of personal data Facebook aggregates about users and makes available to advertisers enables such malicious targeting.

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Published In

FAT* '19: Proceedings of the Conference on Fairness, Accountability, and Transparency
January 2019
388 pages
ISBN:9781450361255
DOI:10.1145/3287560
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 29 January 2019

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Author Tags

  1. advertisements
  2. news media
  3. perception bias
  4. social divisiveness
  5. social media
  6. targeting

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Cited By

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  • (2025)Weaponizing the Wall: The Role of Sponsored News in Spreading Propaganda on FacebookSocial Networks Analysis and Mining10.1007/978-3-031-78541-2_27(438-454)Online publication date: 24-Jan-2025
  • (2024)Enhancing Fake News Detection with a Hybrid NLP-Machine Learning FrameworkIECE Transactions on Intelligent Systematics10.62762/TIS.2024.4619431:3(203-214)Online publication date: 12-Dec-2024
  • (2024)Cyber-enabled influence operations as a ‘center of gravity’ in cyberconflict: The example of Russian foreign interference in the 2016 US federal electionJournal of Peace Research10.1177/0022343323122581461:1(10-27)Online publication date: 27-Feb-2024
  • (2024)On the Use of Proxies in Political Ad TargetingProceedings of the ACM on Human-Computer Interaction10.1145/36869178:CSCW2(1-31)Online publication date: 8-Nov-2024
  • (2024)Misinformation Campaigns through WhatsApp and Telegram in Presidential Elections in BrazilCommunications of the ACM10.1145/365332567:8(72-77)Online publication date: 18-Jul-2024
  • (2024)Beyond the Guidelines: Assessing Meta's Political Ad Moderation in the EUProceedings of the 2024 ACM on Internet Measurement Conference10.1145/3646547.3689020(480-487)Online publication date: 4-Nov-2024
  • (2024)The Cost of Reach: Testing the Role of Ad Delivery Algorithms in Online Political CampaignsPolitical Communication10.1080/10584609.2024.2439317(1-33)Online publication date: 23-Dec-2024
  • (2023)Disintermediation and disinformation as a political strategy: use of AI to analyse fake news as Trump’s rhetorical resource on TwitterEl Profesional de la información10.3145/epi.2023.sep.23Online publication date: 24-Oct-2023
  • (2023)Political advertisement on Facebook and Instagram in the run up to 2022 Italian general electionProceedings of the 15th ACM Web Science Conference 202310.1145/3578503.3583598(13-22)Online publication date: 30-Apr-2023
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