{"id":"W2117221896","doi":"10.1111/iere.12275","title":"RUMORS AND SOCIAL NETWORKS","year":2018,"lang":"en","type":"article","venue":"International Economic Review","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research; Agence Nationale de la Recherche; National Science Foundation","keywords":"Incentive; Limit (mathematics); Filter (signal processing); Computer science; Bayesian game; Microeconomics; State (computer science); Transmission (telecommunications); Incentive compatibility; Bayesian probability; Social network (sociolinguistics); Economics; Game theory; Mathematical economics; Repeated game; Artificial intelligence; Telecommunications; Mathematics; Social media; Algorithm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003127877,0.0003776378,0.0005935149,0.001775513,0.0009663312,0.002914523,0.0006032513,0.001853549,0.001988378],"category_scores_gemma":[0.01929589,0.0003065846,0.0003384526,0.001672109,0.002472663,0.004023403,0.0009994712,0.001219086,0.0002113031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001226475,"about_ca_system_score_gemma":0.0004329954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002219654,"about_ca_topic_score_gemma":0.001069133,"domain_scores_codex":[0.9977728,0.001507953,0.00005913766,0.0001726306,0.0003368427,0.000150676],"domain_scores_gemma":[0.9785579,0.01668481,0.002857693,0.0007250753,0.0008256746,0.0003489709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001038507,0.00006783455,0.006736635,0.0004147469,0.0001898791,0.0003858343,0.001540396,0.02690644,0.0007720695,0.9182218,0.004718961,0.03994151],"study_design_scores_gemma":[0.00006254156,0.00008257187,0.007057058,0.0002863101,0.00008891526,0.0004035489,0.0008310073,0.06626321,0.0003713511,0.9023232,0.02218194,0.00004821775],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5622991,0.05198347,0.1874602,0.04196041,0.001018639,0.0001740743,0.0005489987,0.0002459614,0.1543092],"genre_scores_gemma":[0.9855043,0.007891349,0.00350027,0.0003071281,0.0004516743,0.00002731244,0.00004291919,0.00000743495,0.002267461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003127877,"threshold_uncertainty_score":0.01654196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01361455432754459,"score_gpt":0.3045187234465104,"score_spread":0.2909041691189658,"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."}}