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Record W7065793986

Exploring Incel Language and Subreddit Activity on Reddit

2020· article· en· W7065793986 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks -A service of University of Vermont Libraries (University of Vermont) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsResentmentLonelinessIdeologyPopular cultureRomanceSocial mediaChurning
DOInot available

Abstract

fetched live from OpenAlex

Incels, or involuntary celibates, are individuals who struggle socially, due to their inability to have a romantic or sexual relationships. In popular culture, the community is known for churning out memes, strange made-up words, and startling acts of violence. Behind the veil of humor and "relatable content" lies an anti-feminist ideology that channels Incel loneliness into intense resentment towards themselves, women, and society at large. At its most extreme, Inceldom has motivated attacks like the 2014 Isla Vista attack and the 2018 Toronto van attack, resulting in the deaths of six and ten, respectively. To investigate the overall activity of this community, we look at the timeseries of comment activity on three popular Incel forums on Reddit. We then compare the words commented from one of these forums, r/Braincels, to a random Reddit comment corpus using rank divergence. The timeseries of the words that appear more often in r/Braincels indicates that these words may be a fingerprint for Incel communities.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.041
GPT teacher head0.194
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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