{"id":"W4376853834","doi":"10.2139/ssrn.4439793","title":"When Crowds Aren't Wise: Biased Social Networks and its Price Impact","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Western University","funders":"","keywords":"Crowds; Economics; Econometrics; Computer science; Computer security","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":[0.002565453,0.0002374373,0.0005074711,0.00167527,0.001789357,0.005270386,0.0006095472,0.002654866,0.01882804],"category_scores_gemma":[0.04567607,0.0003115367,0.0002475919,0.001852602,0.003098457,0.004861476,0.001635586,0.002249686,0.001319792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001474489,"about_ca_system_score_gemma":0.0005030428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006028197,"about_ca_topic_score_gemma":0.00697574,"domain_scores_codex":[0.9983413,0.0007401477,0.00005113866,0.0002470963,0.0004034627,0.0002167648],"domain_scores_gemma":[0.9598044,0.02953194,0.005578814,0.001394719,0.001665153,0.002025072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001866918,0.001110196,0.279808,0.0004144624,0.0005753072,0.001792937,0.01064443,0.009178067,0.003035377,0.5014076,0.05389094,0.1362757],"study_design_scores_gemma":[0.0002486123,0.0002013556,0.2146707,0.0001700397,0.0002949089,0.0005123289,0.01214476,0.02296575,0.0008963929,0.7086459,0.039104,0.0001451971],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7851224,0.002650032,0.003838189,0.03284493,0.0004841957,0.00004783203,0.0005095403,0.00006393288,0.174439],"genre_scores_gemma":[0.9967718,0.000260732,0.0001120935,0.0004694724,0.0002569324,0.000006918141,0.00002730188,0.0000184874,0.002076322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01882804,"threshold_uncertainty_score":0.06298608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02634183796647083,"score_gpt":0.3388993483232965,"score_spread":0.3125575103568257,"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."}}