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Record W2932779891 · doi:10.1177/1750481319835639

Weaponized iconoclasm in Internet memes featuring the expression ‘Fake News’

2019· article· en· W2932779891 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDiscourse & Communication · 2019
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsThe InternetCybercultureIdeologySocial mediaExpression (computer science)Media studiesInternet privacyPolitical sciencePoliticsSociologyWorld Wide WebComputer scienceLaw

Abstract

fetched live from OpenAlex

The expression ‘Fake News’ inside Internet memes engenders significant online virulence, possibly heralding an iconoclastic emergence of weaponized propaganda for assaulting agencies reared on public trust. Internet memes are multimodal artifacts featuring ideological singularities designed for ‘flash’ consumption, often composed by numerous voices echoing popular, online culture. This study proposes that ‘Fake News’ Internet memes are weaponized iconoclastic multimodal propaganda (WIMP) discourse and attempts to delineate them as such by asking: What power relations and ideologies do Internet memes featuring the expression ‘fake news’ harbor? How might those manifestations qualify as WIMP discourse? A multimodal critical discourse analysis of a small pool of ‘fake news’ Internet memes drawn from four popular social media websites revealed what agencies were often targeted and from what political canons they likely emerged. Findings indicate that many Internet memes featuring ‘fake news’ are specifically directed, revealing an underlying hazard that WIMP discourse could diminish democratic processes while influencing online trajectories of public discourse.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.025
GPT teacher head0.355
Teacher spread0.330 · 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