Bridging the Open Web and APIs: Alternative Social Media Alongside the Corporate Web
Bibliographic record
Abstract
Concentrations of power over the internet among a small number of corporate platforms have motivated attempts to build alternative social media. Using the contemporary internet routinely involves relying on a small number of dominant corporate platforms. In reaction against this centralization of power, there are many attempts to build alternative Web technologies that reconfigure the internet’s power structures and enact their own values. However, given the entrenchment of large corporate platforms, this typically involves co-existing with rather than replacing them, at least in the present. Accordingly, it is important to investigate challenges arising when alternative social media operate alongside and even within the systems to which they propose an alternative. We investigate this through an empirical study of the IndieWeb, a community of personal websites with social networking features including syndication to and from corporate platforms. Using GitHub data, we study the development of a tool for this syndication called Bridgy, focusing on its relationship with the Facebook API. By identifying breakdowns in this relationship, we identify the following challenges: translating differing logics between the open Web and APIs, occasional ambiguity in Facebook’s presentation of privacy settings, and ongoing precarity due to API updates. Our analysis illustrates the reality of maintaining alternative technical systems as part of present-day infrastructures and generates insights for building socially empowering technologies for the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".