{"id":"W3093184805","doi":"10.22215/etd/2019-13842","title":"A comprehensive topic-model based hybrid sentiment analysis system","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Sentiment analysis; Variety (cybernetics); Pipeline (software); Artificial intelligence; Machine learning; Topic model; Data science; Coherence (philosophical gambling strategy); Data mining","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":[0.000879807,0.000898854,0.0007826881,0.001633461,0.0006076828,0.001287196,0.0009402771,0.0006717146,0.005573296],"category_scores_gemma":[0.001500836,0.0003918632,0.0008245289,0.001060948,0.0001396012,0.002012271,0.0009933936,0.0007167531,0.006754091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005373558,"about_ca_system_score_gemma":0.0007284026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002963714,"about_ca_topic_score_gemma":0.003201637,"domain_scores_codex":[0.9995691,0.00005942866,0.0000527344,0.0001480986,0.0001308251,0.00003972463],"domain_scores_gemma":[0.9994832,0.00008413361,0.00004079726,0.00005908676,0.0002850093,0.00004774025],"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":[0.001122457,0.0008217338,0.00973068,0.000662459,0.0004706219,0.0006431178,0.0007837279,0.0123791,0.1363095,0.005915615,0.1523454,0.6788156],"study_design_scores_gemma":[0.0001150219,0.0002152021,0.005451594,0.00004310631,0.0001787264,0.0002474753,0.0002226338,0.9121727,0.02819849,0.005410619,0.04764538,0.00009904343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06256806,0.0009070304,0.7906917,0.001085875,0.0004999779,0.00112649,0.01255914,0.116841,0.0137208],"genre_scores_gemma":[0.3316409,0.0006663856,0.6065851,0.0007478173,0.0004962519,0.001517168,0.03711987,0.002063939,0.01916264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005573296,"threshold_uncertainty_score":0.01864457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788316938010085,"score_gpt":0.2716602899728654,"score_spread":0.2537771205927645,"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."}}