{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003784823,0.002679793,0.001920143,0.002871112,0.0006732726,0.00138493,0.001157351,0.002060485,0.002461093],"category_scores_gemma":[0.009590447,0.0003558848,0.0008584404,0.001417979,0.0005331237,0.002397529,0.001583035,0.001374904,0.001775083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00084107,"about_ca_system_score_gemma":0.0007130312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008120022,"about_ca_topic_score_gemma":0.009245601,"domain_scores_codex":[0.9974031,0.0009339584,0.0003289031,0.0005419221,0.0004939299,0.0002982746],"domain_scores_gemma":[0.994305,0.003153608,0.000374123,0.0004679606,0.001393465,0.0003059439],"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":[0.005965934,0.003146797,0.04712167,0.00117733,0.001191002,0.0005022263,0.000215117,0.1660718,0.01955677,0.001109874,0.01766193,0.7362795],"study_design_scores_gemma":[0.00007693306,0.0008129595,0.005859933,0.00004948585,0.00009793173,0.0001817001,0.0001512772,0.9799958,0.0113213,0.0004348321,0.0009770988,0.00004078658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9168417,0.008187895,0.05567306,0.0009218394,0.001180494,0.0003457195,0.002635939,0.006598763,0.007614636],"genre_scores_gemma":[0.9411972,0.001061174,0.04619701,0.0002193771,0.0001688823,0.0001601241,0.007543772,0.0001358567,0.00331678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008120022,"threshold_uncertainty_score":0.02001631,"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."}}