{"id":"W2791438573","doi":"10.1007/s13042-018-0798-5","title":"Topic specific emotion detection for retweet prediction","year":2018,"lang":"en","type":"article","venue":"International Journal of Machine Learning and Cybernetics","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Sentiment analysis; Computer science; Preference; Task (project management); Field (mathematics); Topic model; Social media; Social network (sociolinguistics); Information retrieval; Data science; World Wide Web; 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":[0.0005358456,0.0008639194,0.0005763294,0.002336327,0.0003741288,0.0007700638,0.0005100279,0.0007045238,0.002735987],"category_scores_gemma":[0.002256002,0.0001613386,0.0004882952,0.001432173,0.0001476539,0.001159213,0.0005069775,0.0008505775,0.002102222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002223744,"about_ca_system_score_gemma":0.0001892334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001498452,"about_ca_topic_score_gemma":0.002959936,"domain_scores_codex":[0.9996071,0.00005985942,0.0000264458,0.0001338676,0.0000998756,0.00007279074],"domain_scores_gemma":[0.9987778,0.0005049395,0.0001495881,0.0001418264,0.0003490055,0.0000768769],"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":[0.001192148,0.0007057508,0.05711965,0.0004135618,0.0003707526,0.0005399457,0.0004485786,0.01988453,0.153256,0.002715335,0.01813444,0.7452193],"study_design_scores_gemma":[0.00002708605,0.0003742728,0.07292537,0.00004862294,0.0002605197,0.0005641347,0.0002712189,0.8809954,0.03203215,0.005116377,0.007324576,0.00006029896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5693297,0.003712093,0.4066103,0.0004937568,0.0007359807,0.0003321228,0.004802253,0.003406519,0.01057727],"genre_scores_gemma":[0.9372474,0.0007778701,0.04891411,0.00008689954,0.0003681834,0.0001474772,0.003435289,0.0001258849,0.008896858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002735987,"threshold_uncertainty_score":0.00915271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008949833579610511,"score_gpt":0.2716502070586415,"score_spread":0.262700373479031,"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."}}