{"id":"W3168420408","doi":"10.1109/access.2021.3088410","title":"Monitoring Cyber SentiHate Social Behavior During COVID-19 Pandemic in North America","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Pandemic; Coronavirus disease 2019 (COVID-19); Sentiment analysis; Social media; Artificial intelligence; Data science; Big data; The Internet; Machine learning; Scale (ratio); Stability (learning theory); Internet privacy; Computer security; World Wide Web; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003238147,0.0003198205,0.0002722075,0.0006564535,0.0004730298,0.0003645282,0.0003433417,0.0003754522,0.0005091106],"category_scores_gemma":[0.0009177431,0.00009854636,0.0001357155,0.0004931989,0.0002542783,0.0005414666,0.0004232639,0.0004066353,0.0001757771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005757342,"about_ca_system_score_gemma":0.0003430893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02502724,"about_ca_topic_score_gemma":0.05616064,"domain_scores_codex":[0.9997819,0.00006170859,0.00001119482,0.00005382801,0.00005158361,0.00003970915],"domain_scores_gemma":[0.9994473,0.0001495663,0.00009980793,0.00003860403,0.0001883211,0.00007638474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003218674,0.0005932667,0.8041523,0.0003002802,0.0001356143,0.00164594,0.003968582,0.02578728,0.01512599,0.001286013,0.02159865,0.1250841],"study_design_scores_gemma":[0.00001101852,0.0001924105,0.7136129,0.00006243003,0.00003748644,0.0002625008,0.006922772,0.2680929,0.003005679,0.0009647103,0.006785919,0.00004944286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923173,0.0001601802,0.003011583,0.000388949,0.00005005756,0.00005920165,0.001186338,0.000165674,0.002660779],"genre_scores_gemma":[0.9943615,0.0001195458,0.002962566,0.00008764527,0.0000261911,0.00004727229,0.001592994,0.000008830291,0.0007933961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02502724,"threshold_uncertainty_score":0.04976314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05117454856832516,"score_gpt":0.334774911543805,"score_spread":0.2836003629754798,"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."}}