{"id":"W4386810309","doi":"10.18280/ria.370413","title":"Enhancing Cyberbullying Detection on Indonesian Twitter: Leveraging FastText for Feature Expansion and Hybrid Approach Applying CNN and BiLSTM","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indonesian; Feature (linguistics); Computer science; Artificial intelligence; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007776289,0.0002661244,0.0002602228,0.00040116,0.0007764817,0.0003711013,0.0002805887,0.0001115663,0.00000195448],"category_scores_gemma":[0.0001025609,0.0002657627,0.00007876322,0.0007667812,0.00005503777,0.0003830609,0.0001817638,0.0003084264,0.00005001599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005610304,"about_ca_system_score_gemma":0.00002275411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000312162,"about_ca_topic_score_gemma":0.000006098061,"domain_scores_codex":[0.9979483,0.00006785641,0.0003374552,0.0008906965,0.0002221066,0.0005335175],"domain_scores_gemma":[0.9989544,0.0002383156,0.0001319044,0.000455679,0.00007344141,0.0001462176],"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":[0.00004093712,0.00004973621,0.0001583486,0.0002413455,0.00002122052,0.00002156824,0.003691565,0.006791064,0.1543647,0.000725332,0.0001176168,0.8337765],"study_design_scores_gemma":[0.00008388946,0.0001458209,0.0001155529,0.0001348215,0.000008435412,0.00009765182,0.001176844,0.5536605,0.4422106,0.0009237081,0.001165561,0.0002765928],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3314803,0.0001050531,0.6667483,0.0002903868,0.0003270485,0.0005617011,0.000001532287,0.0003023067,0.000183364],"genre_scores_gemma":[0.9893895,0.0001097139,0.009401066,0.000157811,0.000156574,0.0002122217,0.000009780154,0.0000325725,0.0005307022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8335,"threshold_uncertainty_score":0.9999794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03319803522907172,"score_gpt":0.2519311943709145,"score_spread":0.2187331591418428,"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."}}