{"id":"W3045420183","doi":"10.1177/2053951720938405","title":"Going viral: How a single tweet spawned a COVID-19 conspiracy theory on Twitter","year":2020,"lang":"en","type":"article","venue":"Big Data & Society","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":216,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Canadian Institutes of Health Research","keywords":"Misinformation; Social media; Hoax; Disinformation; Coronavirus disease 2019 (COVID-19); Politics; Pandemic; Power (physics); Fake news; Media studies; Internet privacy; Vetting; Political science; Flagging; Public relations; Sociology; Law; Computer science; History; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003521329,0.0007015222,0.0003730078,0.002545508,0.01129668,0.01076923,0.001052018,0.003328584,0.007178537],"category_scores_gemma":[0.01763394,0.0006388442,0.0006164901,0.001956978,0.009531979,0.01567403,0.005619165,0.00404242,0.002464994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00288927,"about_ca_system_score_gemma":0.001478747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132162,"about_ca_topic_score_gemma":0.01500352,"domain_scores_codex":[0.995946,0.002318444,0.0001193315,0.000477624,0.0007650983,0.0003735712],"domain_scores_gemma":[0.9899593,0.006450953,0.001198791,0.0007944776,0.0008642984,0.0007321961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003978955,0.0001381959,0.05602904,0.0004757991,0.0001078178,0.007484413,0.4905968,0.001756712,0.006574451,0.2926551,0.06320506,0.08057874],"study_design_scores_gemma":[0.00007864538,0.0002665155,0.02534995,0.0007589629,0.0001378641,0.00337883,0.2822894,0.01584179,0.002996347,0.1344459,0.53411,0.0003458384],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5514905,0.002575898,0.04293574,0.08046169,0.002419363,0.0004039237,0.001092325,0.0007973901,0.3178232],"genre_scores_gemma":[0.9691664,0.0007545942,0.004628554,0.004794565,0.000481895,0.0001205679,0.000277823,0.0003301351,0.01944551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01132162,"threshold_uncertainty_score":0.02401465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3614947129742199,"score_gpt":0.3813251228364761,"score_spread":0.0198304098622562,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}