{"id":"W2984263896","doi":"10.32877/bt.v2i1.92","title":"Extraction Opinion of Social Media in Higher Education Using Sentiment Analysis","year":2019,"lang":"en","type":"article","venue":"bit-Tech","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Sentiment analysis; Social media; Political science; Advertising; Media studies; Computer science; Sociology; Artificial intelligence; Business; 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":[0.0005810119,0.0003701233,0.0002729258,0.002862911,0.0004128219,0.001160688,0.0001527057,0.0002970304,0.001805957],"category_scores_gemma":[0.001907627,0.0001063217,0.0004747588,0.002057727,0.0001467172,0.0009323623,0.0003104805,0.0002466276,0.001414535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004217922,"about_ca_system_score_gemma":0.0003476563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001310984,"about_ca_topic_score_gemma":0.001938704,"domain_scores_codex":[0.9994498,0.000111328,0.00008113017,0.00006544531,0.0002246537,0.00006760687],"domain_scores_gemma":[0.9991048,0.0002242367,0.0001473087,0.00002861598,0.00046511,0.00002991794],"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":[0.0007001816,0.0004373838,0.1204671,0.001164445,0.0001802042,0.001926233,0.002893094,0.002544542,0.1138171,0.004407655,0.02248259,0.7289795],"study_design_scores_gemma":[0.0000730157,0.0009796178,0.5351015,0.0007031786,0.0005777171,0.002361371,0.01807627,0.2174468,0.1080776,0.009994971,0.1064308,0.0001771685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8560007,0.001184243,0.09506795,0.001577324,0.0004982392,0.0006785992,0.00833625,0.0007721691,0.03588452],"genre_scores_gemma":[0.9480301,0.0009004621,0.03978269,0.0001621333,0.0003137296,0.0002750102,0.004054043,0.00004896486,0.006432828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002862911,"threshold_uncertainty_score":0.006041527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05059007995558874,"score_gpt":0.3295014568925162,"score_spread":0.2789113769369275,"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."}}