{"id":"W4406302405","doi":"10.1145/3711912","title":"Unsupervised Framing Analysis for Social Media Discourse in Polarizing Events","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on the Web","topic":"Social Media and Politics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias; Agencia Nacional de Investigación y Desarrollo","keywords":"Computer science; Generalizability theory; Framing (construction); Data science; Social media; Computational sociology; Realm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004159851,0.00008196555,0.0001665771,0.0002331268,0.001013501,0.00003559763,0.0003745657,0.0001266183,0.0001277117],"category_scores_gemma":[0.0005835685,0.00007045011,0.000220053,0.001183483,0.0001605044,0.00007684337,0.000003688331,0.0002007381,0.000007648866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001289327,"about_ca_system_score_gemma":0.0002547333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001258225,"about_ca_topic_score_gemma":0.01297567,"domain_scores_codex":[0.9989559,0.0002237328,0.0001648911,0.0001387025,0.0002118474,0.0003049363],"domain_scores_gemma":[0.9974483,0.002259348,0.00003177221,0.0001722328,0.00004252604,0.00004581965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001825243,0.0009322592,0.06597601,0.00006300285,0.00240116,0.000003616885,0.5933861,0.0003144045,0.001052989,0.2082545,0.0006981132,0.1267354],"study_design_scores_gemma":[0.002678741,0.00005036093,0.0534342,0.0001481507,0.003252042,1.109839e-7,0.6488119,0.001118066,0.001537354,0.2580476,0.03013102,0.0007905245],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9138322,0.00007219532,0.02638905,0.05549534,0.001471655,0.0005567499,0.0001284292,0.00008242996,0.001971919],"genre_scores_gemma":[0.9985796,0.00004509834,0.0002601576,0.0004636531,0.000176709,0.00008216389,0.000005408272,0.000006759584,0.0003805162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1259449,"threshold_uncertainty_score":0.7795134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.050320972927824,"score_gpt":0.3614347509426365,"score_spread":0.3111137780148125,"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."}}