{"id":"W4391385354","doi":"10.2196/47508","title":"Public Opinion About COVID-19 on a Microblog Platform in China: Topic Modeling and Multidimensional Sentiment Analysis of Social Media","year":2024,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Office for Philosophy and Social Sciences","keywords":"Microblogging; Social media; Latent Dirichlet allocation; Public opinion; Sentiment analysis; Topic model; Computer science; Government (linguistics); Pandemic; Data science; Coronavirus disease 2019 (COVID-19); Information retrieval; Artificial intelligence; Political science; World Wide Web; Politics; Medicine; Law","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00144401,0.0005525447,0.0003923616,0.001642309,0.0005898651,0.0007410439,0.0004299597,0.0005122705,0.0007666295],"category_scores_gemma":[0.002422373,0.0001872185,0.0008867461,0.0009047583,0.0002922876,0.0009432624,0.0005099674,0.0004404565,0.0001868356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175071,"about_ca_system_score_gemma":0.000726886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03427723,"about_ca_topic_score_gemma":0.02782949,"domain_scores_codex":[0.9995875,0.0001146304,0.00003195957,0.0000970209,0.00008186982,0.00008705635],"domain_scores_gemma":[0.9989349,0.0004655555,0.0001838884,0.00005186494,0.0002748243,0.00008900365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004138853,0.0005069121,0.8400788,0.0002706141,0.0002593511,0.0008358371,0.004039001,0.03510087,0.009041249,0.001685294,0.005507036,0.1022612],"study_design_scores_gemma":[0.00001310818,0.0001080702,0.3839963,0.00002626602,0.0001091397,0.00006824397,0.002387644,0.6099933,0.00164839,0.0006701606,0.0009400884,0.00003922623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960117,0.00006649506,0.002776754,0.0002419462,0.00001684823,0.00002739505,0.0002718612,0.00001821862,0.0005686919],"genre_scores_gemma":[0.9977797,0.00007626267,0.001000172,0.00002227366,0.00003408109,0.00002691096,0.000519435,0.000004639776,0.000536491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03427723,"threshold_uncertainty_score":0.06815541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1527602165403132,"score_gpt":0.4323322924645032,"score_spread":0.27957207592419,"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."}}