{"id":"W3170767617","doi":"10.21428/594757db.08d5c187","title":"Using Sentiment Information for Preemptive Detection of Harmful Comments in Online Conversations","year":2021,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Research Canada","funders":"Mitacs","keywords":"Conversation; Computer science; Task (project management); Focus (optics); Moderation; Sentiment analysis; Subject (documents); Data science; Artificial intelligence; World Wide Web; Machine learning; Psychology; Engineering; Communication","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002476622,0.001014404,0.0007300225,0.004039288,0.0008378784,0.001152109,0.0004724773,0.0008273129,0.001653723],"category_scores_gemma":[0.0151919,0.0002546736,0.0005019808,0.001408489,0.0003027929,0.001980479,0.0008514812,0.001274833,0.001670561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004018768,"about_ca_system_score_gemma":0.0005747985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00142121,"about_ca_topic_score_gemma":0.002539003,"domain_scores_codex":[0.998262,0.0005596607,0.000155131,0.0002966017,0.0005462665,0.0001804005],"domain_scores_gemma":[0.9865953,0.006536702,0.002350757,0.0007048323,0.003310102,0.0005022978],"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":[0.001906735,0.0008314737,0.2379563,0.001279735,0.0003116644,0.001027903,0.003965427,0.00369584,0.1741731,0.00244616,0.0137354,0.5586701],"study_design_scores_gemma":[0.0001176598,0.001128926,0.3798993,0.0004433168,0.0006330463,0.001892297,0.005153511,0.4533549,0.1171009,0.01185474,0.02810528,0.0003163119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7977458,0.001636385,0.1775666,0.001295645,0.0004779832,0.000754931,0.003802396,0.002727538,0.0139927],"genre_scores_gemma":[0.9218652,0.0004786983,0.07240599,0.0001804342,0.0003477891,0.000189969,0.002364764,0.0001256644,0.002041553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004039288,"threshold_uncertainty_score":0.01309776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05904349977734594,"score_gpt":0.320778489359092,"score_spread":0.2617349895817461,"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."}}