{"id":"W4379521486","doi":"10.21428/594757db.40c1a462","title":"Stock Market Prediction from Sentiment and Financial Stock Data Using Machine Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Sentiment analysis; Stock market; Social media; Stock market prediction; Stock (firearms); Computer science; Convolutional neural network; Financial market; Artificial neural network; Predictive modelling; Machine learning; Artificial intelligence; Finance; Economics; World Wide Web","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":[0.0008300293,0.000802014,0.0005312529,0.001039606,0.0002332172,0.0005836497,0.0003852401,0.000488575,0.001180925],"category_scores_gemma":[0.00214473,0.0002563899,0.0005898125,0.0007415009,0.0001043545,0.0009478204,0.0003348399,0.0007065255,0.000593619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004221327,"about_ca_system_score_gemma":0.0004147231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01270204,"about_ca_topic_score_gemma":0.01647094,"domain_scores_codex":[0.9998248,0.00003321207,0.00001792265,0.0000414154,0.00004830531,0.00003447389],"domain_scores_gemma":[0.9993978,0.0002424543,0.00009291896,0.00004620936,0.0001824411,0.00003819254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004963344,0.001098582,0.1794802,0.0001247897,0.0004383611,0.0002392077,0.0001012492,0.4648962,0.007751499,0.001323244,0.008460795,0.3355896],"study_design_scores_gemma":[0.000004302171,0.00002927332,0.007797772,0.000006863282,0.00001339861,0.000006439333,0.000008547383,0.9907659,0.0007549542,0.0004030465,0.0002048854,0.000004543622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9299242,0.0009280462,0.06040062,0.0008998013,0.0001863903,0.00008162123,0.001932859,0.000959072,0.004687525],"genre_scores_gemma":[0.982312,0.0002645876,0.0137094,0.000065506,0.00009414988,0.00002815914,0.002286191,0.00001361377,0.001226344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01270204,"threshold_uncertainty_score":0.02525622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2485409037535272,"score_gpt":0.4239415997223226,"score_spread":0.1754006959687954,"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."}}