The Case for Alternative Social Media
Open accessAbstract
What are “alternative social media”? How can we distinguish alternative social media from mainstream social media? Why are social media alternatives important? How do they work? Why do people make them? What do they tell us about contemporary corporate social media and its related phenomena: surveillance, privacy, power, self-expression, and sociality? This essay answers these questions by theorizing alternative social media. The empirical data for this alternative social media theory are drawn from previous work on alternative sites such as Diaspora, rstat.us, Twister, GNU social, and the Dark Web Social Network. These cases are used to build a generalized conceptual framework. However, this article does not solely theorize from these examples, but rather seeks to contextualize and historicize alternative social media theory within larger bodies of work. In addition to generalization from examples, the theory is informed by two threads. The first thread is the work of alternative media scholars such as Nick Couldry, Chris Atton, and Clemencia Rodriguez, who have done the historical and theoretical work to define alternative media. The second thread is a synthesis of works exploring the technical side of contemporary media, coming from new fields such as software studies. The threads and empirical analyses of sites such as Diaspora, Quitter, and rstat.us are combined into a theoretical matrix that can account for the processes and technical infrastructures that comprise social media alternatives and explain why they are distinct from sites such as Facebook, Twitter, and Google, as well as why they are important.
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A key promise of decentralization in feed-based social media is the diffusion of governance and moderation responsibilities, allowing individual communities to tailor rules and enforcement mechanisms to their specific needs.
“A key promise of decentralization in feed-based social media is the diffusion of governance and moderation responsibilities [40,48,84,91], allowing individual communities to tailor rules and enforcement mechanisms to their specific needs [47].”
From Seeing the Politics of Decentralized Social Media Protocols (2026) · cites this paper as [47]
Protocols aim to disseminate power to users, reduce reliance on centralized entities, and empower a rich ecosystem of interoperable social media services.
“In this way, protocols aim to disseminate power to users, reduce reliance on centralized entities, and empower a rich ecosystem of interoperable social media services [47,63,75].”
From Seeing the Politics of Decentralized Social Media Protocols (2026) · cites this paper as [47]
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References 34 · Cited by 96
- Authors
- Gehl, R. W.
- Affiliations
- University of Utah (US)
- Corresponding author
- Gehl, Robert W.
- ORCID
- Gehl, Robert W.
- Venue
- Social Media + Society
- Publisher
- SAGE Publications
- Published
- 2015-07-01
- Volume
- 1
- Issue
- 2
- ISSN
- 2056-3051 (ISSN-L)
- OpenAlex
- W2177170445
- Cited by
- 96
- References
- 34
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 8 · 2023: 19 · 2022: 12 · 2021: 6 · 2020: 6 · 2019: 5 · 2018: 1 · 2017: 3 · 2016: 4 · 2015: 1
- FWCI
- 3.44
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Social Media + Society (publishedVersion, cc-by-nc)
- SSRN Electronic Journal (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Communication › Media and Communication Studies
- Keywords
- alternative social media, alternative media, diaspora, corporate social media, surveillance, privacy, power, self-expression, sociality, software studies, technological infrastructure, social media theory
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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