{"id":"W4406194178","doi":"10.1016/j.eswa.2024.126287","title":"Public opinion prediction on social media by using machine learning methods","year":2025,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Humanities and Social Science Fund of Ministry of Education of China; Fundamental Research Funds for the Central Universities; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Computer science; Public opinion; Social media; Artificial intelligence; Machine learning; Sentiment analysis; Support vector machine; Data science; World Wide Web; Political science","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":[0.0009946352,0.0007832648,0.0006038282,0.003372316,0.0004221033,0.001385403,0.0003986546,0.0006557329,0.00228553],"category_scores_gemma":[0.004661196,0.0001902368,0.0006996284,0.001571177,0.0001845178,0.001700765,0.0003898227,0.0008398479,0.0020459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005344768,"about_ca_system_score_gemma":0.000335498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004368882,"about_ca_topic_score_gemma":0.005576352,"domain_scores_codex":[0.9993505,0.0001801117,0.00004077092,0.0001278366,0.0002054893,0.00009536649],"domain_scores_gemma":[0.9968469,0.001663121,0.0003402075,0.0001289548,0.0009314513,0.00008941779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001030516,0.001442728,0.127024,0.0003045928,0.0005833991,0.0005352214,0.0002793435,0.07446167,0.01679552,0.004027404,0.03163201,0.7418836],"study_design_scores_gemma":[0.00001201813,0.00005376666,0.007519256,0.00001339657,0.00004960951,0.00003009187,0.0000659204,0.9867443,0.002304384,0.002234635,0.0009623949,0.0000102739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6609391,0.001493227,0.3120239,0.001591443,0.0006801953,0.0002619486,0.005018922,0.002696014,0.01529521],"genre_scores_gemma":[0.9598538,0.0003575426,0.03308657,0.00009395216,0.0006181388,0.00008288071,0.003027138,0.00004910707,0.002830938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004368882,"threshold_uncertainty_score":0.0086869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07570998929517869,"score_gpt":0.3565352943096752,"score_spread":0.2808253050144965,"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."}}