{"id":"W4296363272","doi":"10.5121/csit.2022.121511","title":"Performance Evaluation for the use of ELMo Word Embedding in Cyberbullying Detection","year":2022,"lang":"en","type":"article","venue":"","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Word2vec; Computer science; Word embedding; Word (group theory); Artificial intelligence; Social media; Natural language processing; The Internet; Key (lock); Embedding; Support vector machine; Machine learning; Speech recognition; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001352837,0.00007070129,0.00008002587,0.0001554597,0.0003941149,0.00006438337,0.0003040386,0.00002142236,0.00004214537],"category_scores_gemma":[0.0001007021,0.00005789188,0.00004880322,0.0006211899,0.00001229908,0.0004912371,0.0001404598,0.0001321418,0.000002119462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001402113,"about_ca_system_score_gemma":0.00005098468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001433476,"about_ca_topic_score_gemma":0.00008031227,"domain_scores_codex":[0.9989086,0.0001071102,0.0002193724,0.0002104561,0.0003774319,0.0001769705],"domain_scores_gemma":[0.9992617,0.0002392177,0.0001024832,0.0002913233,0.00008780337,0.00001740945],"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":[0.00003118975,0.00002363153,0.0004022572,0.000007161218,0.000007140166,2.525472e-7,0.0004354582,0.2220518,0.005327664,0.0002768724,0.00005703224,0.7713796],"study_design_scores_gemma":[0.0002899909,0.0001108751,0.003352413,0.000006750451,0.000006747518,0.000008978352,0.0001214244,0.9793256,0.01250965,0.0001008056,0.004092073,0.00007466655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6574332,0.0000310063,0.3411338,0.000138861,0.0004965048,0.0005612975,7.055627e-7,0.00005462793,0.0001499544],"genre_scores_gemma":[0.9888264,0.000009885714,0.01049171,0.00007040564,0.00002500229,0.0003585101,0.000001182915,0.000006102538,0.0002108142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7713049,"threshold_uncertainty_score":0.3031253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06441875478281359,"score_gpt":0.281362161260077,"score_spread":0.2169434064772634,"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."}}