{"id":"W2573523873","doi":"","title":"User Participation and Honesty in Online Rating Systems: What a Social Network Can Do","year":2016,"lang":"en","type":"article","venue":"Edinburgh Research Explorer (University of Edinburgh)","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Recommender system; Baseline (sea); Incentive; Computer science; Honesty; Dilemma; Online participation; Social network (sociolinguistics); Crowdsourcing; Online community; Filter (signal processing); Rating system; Internet privacy; Data science; World Wide Web; Social media; The Internet; Psychology; Microeconomics; Environmental economics","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":[0.02260214,0.0007190477,0.001316065,0.001124544,0.002742823,0.004608179,0.001275363,0.002647127,0.00393583],"category_scores_gemma":[0.1069753,0.0007012342,0.0008661176,0.001297343,0.003026936,0.01544619,0.003151405,0.00221481,0.0007478594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032785,"about_ca_system_score_gemma":0.001153931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002501905,"about_ca_topic_score_gemma":0.002219592,"domain_scores_codex":[0.9814546,0.01262382,0.0008386298,0.001943369,0.002441603,0.0006979623],"domain_scores_gemma":[0.8481423,0.103295,0.01709802,0.02168402,0.006661481,0.003119195],"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":[0.002175255,0.001215926,0.238014,0.001296794,0.0008650516,0.0009398464,0.01844946,0.05124488,0.0101081,0.321933,0.01013177,0.3436259],"study_design_scores_gemma":[0.0003359856,0.001210706,0.09191835,0.0005200115,0.0005354208,0.001470383,0.004706643,0.3070792,0.006706025,0.5614348,0.02375683,0.0003256509],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6625432,0.002314924,0.2697113,0.02297244,0.0003664518,0.0003913809,0.0005279592,0.0004189262,0.04075349],"genre_scores_gemma":[0.9822878,0.0003092552,0.01471895,0.000318936,0.0001768871,0.00008815259,0.0001116874,0.00004270101,0.001945541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02260214,"threshold_uncertainty_score":0.119533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431412220547272,"score_gpt":0.3830735770927309,"score_spread":0.2399323550380037,"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."}}