{"id":"W4387914178","doi":"10.1109/codit58514.2023.10284166","title":"Sentiment Analysis Using Smoothed Probabilistic-Based Models","year":2023,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Sentiment analysis; Computer science; Probabilistic logic; Cluster analysis; Smoothing; Artificial intelligence; Latent Dirichlet allocation; Dirichlet distribution; Topic model; Statistical model; Machine learning; Hierarchical Dirichlet process; Natural language processing; Data mining; Mathematics","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":[0.002335086,0.0009993779,0.0009876108,0.002243239,0.0006807901,0.002008112,0.00161231,0.001207244,0.003483682],"category_scores_gemma":[0.009911999,0.0006631567,0.002203998,0.00186849,0.0008152401,0.00340765,0.001057726,0.002066517,0.002824374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054058,"about_ca_system_score_gemma":0.001130591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004786818,"about_ca_topic_score_gemma":0.005820625,"domain_scores_codex":[0.998379,0.0005100759,0.0001015267,0.0004221477,0.0004958421,0.00009145802],"domain_scores_gemma":[0.9970169,0.001803452,0.0002614974,0.0002986924,0.000569643,0.00004977347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002525905,0.0001687878,0.004760058,0.0002510708,0.0003947075,0.0001787679,0.0004693199,0.5504155,0.008430295,0.09757234,0.01198973,0.3251169],"study_design_scores_gemma":[0.000007711542,0.00001618834,0.0004006312,0.000009819476,0.00001569543,0.00002913763,0.00001617101,0.9603364,0.0005096383,0.03666536,0.001979443,0.00001378199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006425377,0.0001959323,0.990453,0.0003595109,0.00006122276,0.00005730372,0.0001974891,0.0006958824,0.001554256],"genre_scores_gemma":[0.4514236,0.001026703,0.5333543,0.0007154862,0.0006036906,0.0005877529,0.002571379,0.0004588707,0.009258118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004786818,"threshold_uncertainty_score":0.01234925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07229150159583578,"score_gpt":0.3028421812544118,"score_spread":0.230550679658576,"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."}}