{"id":"W3216042640","doi":"10.1038/s41586-021-04167-x","title":"Quantifying social organization and political polarization in online platforms","year":2020,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Social Media and Politics","field":"Social Sciences","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Polarization (electrochemistry); Politics; Ideology; Social media; Presidential system; Presidential election; Sociology; Data science; Political science; Computer science; Internet privacy; World Wide Web; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004765787,0.00005761711,0.00009137391,0.00004968506,0.0002682658,0.00002474294,0.00009076329,0.0001178071,0.00004154355],"category_scores_gemma":[0.0004135548,0.00007060511,0.00001667268,0.0007488134,0.0001622089,0.0002278261,0.00003467062,0.0001086989,0.00001203757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009637147,"about_ca_system_score_gemma":0.0001155964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009938092,"about_ca_topic_score_gemma":0.0007186548,"domain_scores_codex":[0.9994136,0.00005059129,0.0000769298,0.0001581075,0.00005681148,0.000243935],"domain_scores_gemma":[0.9996313,0.00007995505,0.00003206929,0.00002971583,0.00006052008,0.0001663832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000004939032,0.00001584496,0.346501,0.000005251592,0.000002780351,0.00001074009,0.007194769,0.00001226987,0.00008046092,0.6461038,0.00001039615,0.00005776747],"study_design_scores_gemma":[0.004271368,0.0002055452,0.3265769,0.00005697921,0.0001936837,0.000002530219,0.5438351,0.02223662,0.0008710029,0.09446388,0.005915167,0.001371214],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962037,0.000004522011,0.001219292,0.001697973,0.0000790257,0.0000757768,0.000007922914,0.00005736606,0.0006544537],"genre_scores_gemma":[0.9990219,0.00002175671,0.00002837611,0.0005487839,0.0003055589,3.74408e-8,0.00001892676,0.000007218528,0.00004739057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.55164,"threshold_uncertainty_score":0.2879193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.14430477263489,"score_gpt":0.2505718024478239,"score_spread":0.1062670298129339,"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."}}