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User Voices, Platform Choices: Social Media Policy Puzzle with Decentralization Salt

Published: 11 May 2024 Publication History

Abstract

In the current digital era, social media platforms wield crucial influence, with the potential for biased content moderation. Considering this risk, we propose a decentralized social media policy-making in this work. The noticeable difference between people’s preferences and X’s established policies in a preliminary study motivates us to design a similar website to collect more comprehensive data in a diverse community. Consequently, N=110 individuals from diverse backgrounds participated in our primary experiment to decide about content moderation on social media. For this purpose, 546 tweets in 3 categories are investigated, 3032 records are captured, and the effect of personal favor on content moderation is analyzed. Furthermore, we propose a novel AI-based method to learn the recommended policy of participants and achieve an accuracy of 79%. Also, by considering the suggested policy of 5 Large Language Models, it is illustrated that they cannot be the decision-makers on democratic social media platforms.

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cover image ACM Conferences
CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
May 2024
4761 pages
ISBN:9798400703317
DOI:10.1145/3613905
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 11 May 2024

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Author Tags

  1. Content Censorship
  2. Decentralization
  3. Decentralized Policy
  4. Social Media
  5. Social Network

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