"At the End of the Day Facebook Does What It Wants": How Users Experience Contesting Algorithmic Content Moderation

Kristen Vaccaro, Christian Sandvig, Karrie Karahalios

Research output: Contribution to journalArticlepeer-review

Abstract

Interest has grown in designing algorithmic decision making systems for contestability. In this work, we study how users experience contesting unfavorable social media content moderation decisions. A large-scale online experiment tests whether different forms of appeals can improve users' experiences of automated decision making. We study the impact on users' perceptions of the Fairness, Accountability, and Trustworthiness of algorithmic decisions, as well as their feelings of Control (FACT). Surprisingly, we find that none of the appeal designs improve FACT perceptions compared to a no appeal baseline. We qualitatively analyze how users write appeals, and find that they contest the decision itself, but also more fundamental issues like the goal of moderating content, the idea of automation, and the inconsistency of the system as a whole. We conclude with suggestions for-as well as a discussion of the challenges of-designing for contestability.

Original languageEnglish (US)
Article number167
JournalProceedings of the ACM on Human-Computer Interaction
Volume4
Issue numberCSCW2
DOIs
StatePublished - Oct 14 2020

Keywords

  • algorithmic experience
  • content moderation

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Human-Computer Interaction
  • Computer Networks and Communications

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