{"id":"W4311175910","doi":"10.36227/techrxiv.21699203.v1","title":"Aspect Based Sentiment Analysis - Twitter","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Sentiment analysis; Popularity; Computer science; Categorization; Social media; Service (business); Product (mathematics); Data science; Set (abstract data type); Analytics; World Wide Web; Artificial intelligence; Business; Psychology; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006471421,0.0003183275,0.0005897688,0.001169614,0.0001851145,0.0006291366,0.001903243,0.00009649921,0.01661324],"category_scores_gemma":[0.000007017105,0.0002927574,0.001183033,0.001743202,0.00001835772,0.0001016945,0.003389305,0.0004404988,0.0001228299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001541002,"about_ca_system_score_gemma":0.0001305973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001570963,"about_ca_topic_score_gemma":0.00001129912,"domain_scores_codex":[0.9968598,0.0001993232,0.0005018024,0.001174087,0.0009325154,0.0003324602],"domain_scores_gemma":[0.9974965,0.00007855159,0.0003097047,0.001934185,0.00006552545,0.0001154833],"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":[0.00001879452,0.001217335,0.1547995,0.0001271804,0.02341193,0.0002623818,0.002171295,0.6695508,0.0001661618,0.02756461,0.1121628,0.008547282],"study_design_scores_gemma":[0.0001880887,0.00002268082,0.005445701,0.00000832858,0.0009220314,3.545883e-7,0.00005796108,0.9774045,0.0004708068,0.0005576633,0.01441969,0.000502185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006095852,0.0001895905,0.9691613,0.002833165,0.0009724519,0.0002041126,0.000006251608,0.000320961,0.02021628],"genre_scores_gemma":[0.7744275,0.0000211345,0.1979151,0.004665695,0.0002660938,0.0001861416,0.0004949732,0.00003851547,0.02198481],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7712463,"threshold_uncertainty_score":0.9999524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03826630628439207,"score_gpt":0.2991238854044829,"score_spread":0.2608575791200908,"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."}}