{"id":"W3171261489","doi":"10.2196/24435","title":"COVID-19 Vaccine–Related Discussion on Twitter: Topic Modeling and Sentiment Analysis","year":2021,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":360,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Social media; Vaccination; Cornerstone; Pandemic; Topic model; Public health; Herd immunity; Coronavirus disease 2019 (COVID-19); Medicine; Psychology; Computer science; World Wide Web; Artificial intelligence; Immunology; Infectious disease (medical specialty); History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003184163,0.0007788623,0.000586988,0.003166888,0.0006903925,0.001561134,0.0005197246,0.0006160056,0.002177725],"category_scores_gemma":[0.008152635,0.0002986997,0.00161637,0.002387978,0.0003348617,0.001564553,0.0009693478,0.0009377336,0.001295386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008765842,"about_ca_system_score_gemma":0.000567832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006382718,"about_ca_topic_score_gemma":0.007150706,"domain_scores_codex":[0.9984655,0.0007283326,0.0001537281,0.0003000032,0.0002199576,0.0001323698],"domain_scores_gemma":[0.9951102,0.003648415,0.0004762409,0.000152726,0.0004866734,0.0001256182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001686684,0.0009885144,0.4809998,0.002642189,0.0009684776,0.00119452,0.01821883,0.04428807,0.02323074,0.009005013,0.06249886,0.3542783],"study_design_scores_gemma":[0.00008692394,0.0002409666,0.1996313,0.0002172031,0.0003331168,0.000308724,0.006370088,0.7532995,0.005227805,0.008031929,0.02612545,0.0001270731],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8954037,0.001266829,0.06282572,0.003057689,0.0003797158,0.001083839,0.02588121,0.00117043,0.00893083],"genre_scores_gemma":[0.9311218,0.0006465688,0.04716794,0.0001956636,0.0003910736,0.001171258,0.01637231,0.0001426139,0.002790874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006382718,"threshold_uncertainty_score":0.01683968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09121144644849306,"score_gpt":0.4613156341040951,"score_spread":0.370104187655602,"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."}}