{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002837877,0.00006261718,0.0001141152,0.0001957138,0.0001625772,0.000040914,0.000252822,0.000145974,0.00005496266],"category_scores_gemma":[0.0002138284,0.00006907053,0.00002068295,0.0004153853,0.0007169818,0.0001021301,0.00006641255,0.0001940297,0.00001147483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002313493,"about_ca_system_score_gemma":0.00006172794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001235895,"about_ca_topic_score_gemma":0.005858766,"domain_scores_codex":[0.9990314,0.000381976,0.000174553,0.0001300902,0.00009201601,0.0001899609],"domain_scores_gemma":[0.9988732,0.0005111924,0.00004081861,0.0004598946,0.00005730217,0.00005755745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009981393,0.0001421967,0.3546587,0.00003697364,0.00004254845,0.00001153665,0.2416798,4.192386e-7,0.001305308,0.3943799,0.004190229,0.003542405],"study_design_scores_gemma":[0.000598998,0.00008558899,0.1863402,0.0001983993,0.00007154867,0.00001242279,0.01101492,0.0002088663,0.000241471,0.02559488,0.7753317,0.000300926],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9550682,0.001563465,0.0001918963,0.02487722,0.0006678104,0.0002232995,0.00001350064,0.00008253852,0.01731212],"genre_scores_gemma":[0.9951321,0.002961456,0.0005056112,0.0006660456,0.0001072527,0.00001530283,0.00002029441,0.00001064333,0.0005812802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7711415,"threshold_uncertainty_score":0.3269329,"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."}}