"Algorithms ruin everything": #RIPTwitter, Folk Theories, and Resistance to Algorithmic Change in Social Media
Open accessAbstract
As algorithmically-driven content curation has become an increasingly common feature of social media platforms, user resistance to algorithmic change has become more frequent and visible. These incidents of user backlash point to larger issues such as inaccurate understandings of how algorithmic systems work as well as mismatches between designer and user intent. Using a content analysis of 102,827 tweets from #RIPTwitter, a recent hashtag-based backlash to rumors about introducing algorithmic curation to Twitter's timeline, this study addresses the nature of user resistance in the form of the complaints being expressed, folk theories of the algorithmic system espoused by users, and how these folk theories potentially frame user reactions. We find that resistance to algorithmic change largely revolves around expectation violation, with folk theories acting as frames for reactions such that more detailed folk theories are expressed through more specific reactions to algorithmic change.
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Algorithmic distribution ties in with other studies of user perception and folk theories about curation algorithms, where users puzzle over distribution of content.
“Algorithmic distribution ties in with other studies of user perception and folk theories about curation algorithms (Alvarado et al. 2020; DeVito et al. 2017; Eslami et al. 2016), where users puzzle over the distribution of content.”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as DeVito et al. 2017
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- Authors
- DeVito, M. A., Gergle, D., & Birnholtz, J.
- Affiliations
- Northwestern University (US)
- Venue
- Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2017-05-02
- Pages
- 3163-3174
- OpenAlex
- W2611145892
- Cited by
- 311
- References
- 8
- Citations by year
- 2026: 66 · 2025: 55 · 2024: 44 · 2023: 36 · 2022: 34 · 2021: 32 · 2020: 11 · 2019: 22 · 2018: 10 · 2017: 1
- FWCI
- 27.75
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- National Science Foundation (IIS-1217143/003)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- algorithmic curation, user resistance, expectancy violation, social networking sites
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