Far-right virtual communities: Exploring users and uses of far-right pages on social media
Bibliographic record
Abstract
The role of social media in facilitating far-right networks and propagating far-right narratives is increasingly documented. However, research tends to focus on far-right pages on social media, thus leaving the users of these pages understudied. Relying on interviews with users of the Facebook page of the radical right organization La Meute in Canada, this study investigates individuals’ motivations and practices when using far-right pages on social media, as well as the interplay between their use of these pages and their view of themselves and society. It shows that users of La Meute’s Facebook page perceive (to varying degrees) that mainstream media are biased and do not represent their views nor address their concerns about immigration issues. As such, they seek meaning by using far-right pages on social media, either as their main source of information or to complement mainstream media. On these pages, they encounter a virtual community of like-minded people, which is conceived in opposition to the rest of society who would not be critical enough of mainstream media and immigration. Boundaries delineating the virtual community tend to be particularly pronounced among individuals who use far-right pages on social media as their main source of information.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".