{"id":"W4392128876","doi":"10.1038/s44271-024-00062-z","title":"Twitter (X) use predicts substantial changes in well-being, polarization, sense of belonging, and outrage","year":2024,"lang":"en","type":"article","venue":"Communications Psychology","topic":"Social Media and Politics","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Government of Canada","keywords":"Outrage; Polarization (electrochemistry); Politics; Social media; Psychology; Social psychology; Personality; Political science; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005575752,0.0001555125,0.0001526615,0.0003346405,0.0003342777,0.000791165,0.0001154947,0.0003593772,0.002964423],"category_scores_gemma":[0.003014512,0.0001341927,0.0003123986,0.000345189,0.0002341986,0.0005706664,0.0006104762,0.0004426175,0.0004978753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001357983,"about_ca_system_score_gemma":0.00009831526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001933499,"about_ca_topic_score_gemma":0.003490089,"domain_scores_codex":[0.9997758,0.00009440578,0.00002126815,0.00004041825,0.00003435889,0.00003379071],"domain_scores_gemma":[0.9978076,0.0005411764,0.001058438,0.0001410813,0.0001652791,0.0002865113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001326706,0.00006272501,0.9939918,0.00002353994,0.00005512746,0.00002471111,0.0007272757,0.00004540127,0.0005875638,0.00004682584,0.0002508821,0.004051425],"study_design_scores_gemma":[0.000001743798,0.00004964386,0.9982023,0.000006054491,0.0000136287,0.00003565518,0.001024471,0.0001548367,0.0001354596,0.00004240154,0.0003300137,0.0000037421],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988731,0.00005706172,0.00007047566,0.00006953414,0.000007346198,0.000005504027,0.0002287511,0.000003133123,0.0006850709],"genre_scores_gemma":[0.9992715,0.0000524081,0.00009306613,0.0000276254,0.000008447597,0.000008726823,0.0002220829,0.000001879523,0.0003142327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002964423,"threshold_uncertainty_score":0.009917021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05598392760955541,"score_gpt":0.392032553624531,"score_spread":0.3360486260149756,"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."}}