{"id":"W2579586109","doi":"10.1109/wi.2016.0020","title":"Discovering Credible Twitter Users in Stock Market Domain","year":2016,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Credibility; Social media; Stock (firearms); Stock market; Computer science; Business; Econometrics; World Wide Web; Economics; Engineering","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":[0.001552911,0.0003571504,0.0003333919,0.003723668,0.0004261656,0.00109841,0.0003092566,0.0006658302,0.001308131],"category_scores_gemma":[0.01487191,0.0001865279,0.0002355417,0.001431616,0.0002514137,0.00232494,0.0007703321,0.0004168804,0.0005267757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003128666,"about_ca_system_score_gemma":0.0002198649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002740974,"about_ca_topic_score_gemma":0.003546352,"domain_scores_codex":[0.9991704,0.0002586665,0.0000776497,0.0001646536,0.0002426841,0.00008593956],"domain_scores_gemma":[0.9888527,0.007729435,0.001718601,0.0004869255,0.0009029217,0.0003092825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007062315,0.0001951907,0.8907998,0.000216308,0.000164154,0.0006376341,0.00216692,0.005801427,0.009039923,0.002037925,0.002408983,0.08582556],"study_design_scores_gemma":[0.00003868977,0.0002811254,0.6066867,0.0001359711,0.000207148,0.001119924,0.00540556,0.3588742,0.0157296,0.004992914,0.006442216,0.00008587974],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889523,0.0002596201,0.006649869,0.0002253279,0.00001757612,0.00003686243,0.0009043169,0.00007686293,0.00287731],"genre_scores_gemma":[0.9973925,0.00008257932,0.001703878,0.00001236341,0.00003077661,0.00001338196,0.0004335407,0.000005260359,0.0003256412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003723668,"threshold_uncertainty_score":0.008212686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1343801012234399,"score_gpt":0.4020701307179368,"score_spread":0.2676900294944968,"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."}}