{"id":"W3155208491","doi":"10.48550/arxiv.2104.09586","title":"Semantic Knowledge Discovery and Discussion Mining of Incel Online Community: Topic modeling","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Data science; Sentiment analysis; Latent semantic analysis; Information retrieval; Topic model; Question answering; World Wide Web; Knowledge extraction; Artificial intelligence","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":[0.003656883,0.0006984569,0.0006911811,0.007471973,0.001173027,0.002212601,0.001397443,0.001347472,0.001340675],"category_scores_gemma":[0.01088278,0.0003557583,0.001856837,0.004746495,0.0007989369,0.003769435,0.001291706,0.001470899,0.000617934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001277502,"about_ca_system_score_gemma":0.001215215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005163534,"about_ca_topic_score_gemma":0.006115543,"domain_scores_codex":[0.9971411,0.001227997,0.0002374726,0.0007532132,0.0004340153,0.0002062216],"domain_scores_gemma":[0.992223,0.005433133,0.0008108306,0.0004853701,0.0008198726,0.0002278636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001321243,0.002084228,0.1484273,0.001952072,0.0009862912,0.001647748,0.01943654,0.08445945,0.02595795,0.07211451,0.02112503,0.6204876],"study_design_scores_gemma":[0.00007317953,0.0001057104,0.02432918,0.0001090333,0.0001582328,0.0003098878,0.003219066,0.8916084,0.005643594,0.06146164,0.01292002,0.00006213396],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3722333,0.001552536,0.6101784,0.002604729,0.0001339537,0.0007091486,0.005526759,0.001104737,0.005956404],"genre_scores_gemma":[0.8154549,0.0005839578,0.1746273,0.0001649191,0.0002364415,0.0007123652,0.005826039,0.00008697764,0.00230704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007471973,"threshold_uncertainty_score":0.01933968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1184357934533684,"score_gpt":0.2281354464083122,"score_spread":0.1096996529549438,"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."}}