{"id":"W4207039276","doi":"10.1109/asew52652.2021.00053","title":"Learning Sentiment Analysis for Accessibility User Reviews","year":2021,"lang":"en","type":"article","venue":"","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Sentiment analysis; Naive Bayes classifier; Popularity; Support vector machine; tf–idf; Artificial intelligence; Machine learning; Bag-of-words model; Boosting (machine learning); Information retrieval; Term (time)","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":[0.001418013,0.001308118,0.0009504312,0.003434258,0.000417813,0.0009012707,0.0004198376,0.0006242007,0.001443194],"category_scores_gemma":[0.005285263,0.0001960877,0.001005099,0.001349172,0.0001710426,0.001033024,0.0004840259,0.0006655948,0.00182778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000665813,"about_ca_system_score_gemma":0.0005569686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003148766,"about_ca_topic_score_gemma":0.005610199,"domain_scores_codex":[0.9986259,0.0003256753,0.0001726065,0.0003037313,0.0004478954,0.0001243253],"domain_scores_gemma":[0.9970464,0.0008916798,0.000402919,0.0001370216,0.001401222,0.0001207397],"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":[0.001036539,0.0009610209,0.1015467,0.001191961,0.0005577217,0.0008540653,0.0007009782,0.0103218,0.03521978,0.001116563,0.06880727,0.7776855],"study_design_scores_gemma":[0.0001267135,0.0008035431,0.1231019,0.0002270284,0.0003581379,0.0009062407,0.00131308,0.8106484,0.0235706,0.002488475,0.03636078,0.00009512336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8033671,0.006870009,0.1434351,0.00172828,0.001280086,0.001367063,0.02163863,0.005468856,0.01484497],"genre_scores_gemma":[0.8853352,0.001217822,0.07845093,0.0002801014,0.0006475227,0.0006114693,0.02763242,0.0001363548,0.005688223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003434258,"threshold_uncertainty_score":0.007499218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06717810131145494,"score_gpt":0.3932527963324494,"score_spread":0.3260746950209944,"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."}}