How Do Users Experience Moderation?: A Systematic Literature Review

Author:

Ma Renkai1ORCID,You Yue1ORCID,Gui Xinning2ORCID,Kou Yubo1ORCID

Affiliation:

1. Pennsylvania State University, State College, PA, USA

2. Pennsylvania State University, University Park, PA, USA

Abstract

Researchers across various fields have investigated how users experience moderation through different perspectives and methodologies. At present, there is a pressing need of synthesizing and extracting key insights from prior literature to formulate a systematic understanding of what constitutes a moderation experience and to explore how such understanding could further inform moderation-related research and practices. To answer this question, we conducted a systematic literature review (SLR) by analyzing 42 empirical studies related to moderation experiences and published between January 2016 and March 2022. We describe these studies' characteristics and how they characterize users' moderation experiences. We further identify five primary perspectives that prior researchers use to conceptualize moderation experiences. These findings suggest an expansive scope of research interests in understanding moderation experiences and considering moderated users as an important stakeholder group to reflect on current moderation design but also pertain to the dominance of the punitive, solutionist logic in moderation and ample implications for future moderation research, design, and practice.

Funder

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

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

Reference122 articles.

1. Julia Alexander. 2019. YouTube moderation bots punish videos tagged as 'gay' or 'lesbian ' study finds. The Verge. Retrieved from https://www.theverge.com/2019/9/30/20887614/youtube-moderation-lgbtq-demonetization-terms-words-nerd-city-investigation Julia Alexander. 2019. YouTube moderation bots punish videos tagged as 'gay' or 'lesbian ' study finds. The Verge. Retrieved from https://www.theverge.com/2019/9/30/20887614/youtube-moderation-lgbtq-demonetization-terms-words-nerd-city-investigation

2. Street-Level Algorithms

3. The Shadowban Cycle: an autoethnography of pole dancing, nudity and censorship on Instagram

4. Disappearing acts: Content moderation and emergent practices to preserve at-risk human rights–related content

5. Problematic Machine Behavior

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