{"id":"W4389493777","doi":"10.31577/cai_2023_4_993","title":"Deep Learning Based Misogynistic Bangla Text Identification from Social Media","year":2023,"lang":"en","type":"article","venue":"Computing and Informatics","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bengali; Hatred; Social media; Artificial intelligence; Computer science; Identification (biology); Deep learning; Confusion matrix; Hostility; Intimidation; Machine learning; Natural language processing; Psychology; World Wide Web; Social psychology; Political science","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":[0.0003664435,0.0008743744,0.0003474859,0.001451364,0.0005430228,0.0008087414,0.0004813431,0.0007135546,0.001830869],"category_scores_gemma":[0.001371813,0.0001498716,0.0004155885,0.0008131008,0.0003003952,0.0009769351,0.0007082816,0.0006600432,0.001805927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005379622,"about_ca_system_score_gemma":0.0004241487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005269161,"about_ca_topic_score_gemma":0.01108548,"domain_scores_codex":[0.9996275,0.00007889978,0.00003412692,0.0001096775,0.00006808706,0.00008174858],"domain_scores_gemma":[0.9992448,0.0003231229,0.00009142175,0.00006322841,0.0002281714,0.00004942941],"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":[0.0009892181,0.0006721296,0.04536572,0.0005622753,0.0001559114,0.002230009,0.001560927,0.02440578,0.06542461,0.00181173,0.02808934,0.8287324],"study_design_scores_gemma":[0.00002817695,0.0003066133,0.04340177,0.0001036131,0.0001122044,0.0008484811,0.002816646,0.8934308,0.042202,0.002533102,0.01415204,0.0000645668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9033876,0.001189231,0.0732652,0.0009353628,0.0004443852,0.0002540906,0.005486326,0.002757099,0.01228082],"genre_scores_gemma":[0.9405025,0.0004266504,0.03613273,0.0001886413,0.0001219268,0.0001150505,0.008256039,0.00007667617,0.01417982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005269161,"threshold_uncertainty_score":0.01047701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01366158206172726,"score_gpt":0.2320620642814693,"score_spread":0.2184004822197421,"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."}}