{"id":"W2556427464","doi":"10.1016/j.inffus.2016.11.011","title":"Fusing and mining opinions for reputation generation","year":2016,"lang":"en","type":"article","venue":"Information Fusion","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Reputation; Computer science; Popularity; Sentiment analysis; Generality; Preference; Public opinion; Principal (computer security); The Internet; Data science; World Wide Web; Information retrieval; Artificial intelligence; Psychology; Computer security; Mathematics","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":[0.002714667,0.001070212,0.001239181,0.004602218,0.0007845049,0.001613924,0.0008677072,0.001055213,0.002429305],"category_scores_gemma":[0.01077467,0.0003261347,0.001085865,0.002899639,0.0002443209,0.002506853,0.0009524684,0.001024574,0.001870631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005924914,"about_ca_system_score_gemma":0.0007213462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001704305,"about_ca_topic_score_gemma":0.003199597,"domain_scores_codex":[0.997769,0.000515757,0.0002280446,0.0003906264,0.0009166495,0.0001799346],"domain_scores_gemma":[0.995139,0.001503325,0.0004859093,0.0004090888,0.002260972,0.0002016932],"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":[0.0006266124,0.000578719,0.01641497,0.000352668,0.0004549086,0.0003874708,0.0004905974,0.01881704,0.044506,0.00549474,0.01525283,0.8966236],"study_design_scores_gemma":[0.00003157457,0.0003745397,0.01013895,0.00005729036,0.0003650274,0.0002243712,0.0003338747,0.9460776,0.02348959,0.01312672,0.005701976,0.00007848165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1407071,0.001270489,0.844663,0.001229582,0.0004573059,0.0003420535,0.001140348,0.002265127,0.007925064],"genre_scores_gemma":[0.7701158,0.0004717218,0.2238711,0.0001547079,0.0004348753,0.0001416273,0.001509073,0.0001246485,0.003176433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004602218,"threshold_uncertainty_score":0.01435667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02967303705003585,"score_gpt":0.2670219949253554,"score_spread":0.2373489578753196,"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."}}