{"id":"W4414606289","doi":"10.17615/veqw-py41","title":"How do social media feed algorithms affect attitudes and behavior in an election campaign?","year":2025,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Social Media and Politics","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Stanford Institute for Economic Policy Research; York University; John Simon Guggenheim Memorial Foundation; Charles Koch Foundation; Nutrition Obesity Research Center, University of North Carolina; University of Wisconsin-Madison; John S. and James L. Knight Foundation; Alfred P. Sloan Foundation","keywords":"Affect (linguistics); Ideology; Politics; Content (measure theory); Social media; Sample (material); Key (lock)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001614605,0.0001044119,0.0001763905,0.0001341149,0.000550601,0.0006067337,0.0001326534,0.0002012864,0.00002697992],"category_scores_gemma":[0.0004366157,0.000105241,0.00003507915,0.0004362078,0.000545325,0.0007870517,0.0000348916,0.000153105,0.000001481116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006604209,"about_ca_system_score_gemma":0.0003151316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008888296,"about_ca_topic_score_gemma":0.006227268,"domain_scores_codex":[0.9989252,0.0002600311,0.0001039489,0.0001839608,0.000212826,0.0003140404],"domain_scores_gemma":[0.99931,0.0004617825,0.00003627106,0.00006427662,0.00003783941,0.00008989043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001729396,0.0001044137,0.3529681,0.00002300262,0.00001173684,0.000006360853,0.09720869,3.469107e-8,0.0001669578,0.5296246,0.000905082,0.0189638],"study_design_scores_gemma":[0.0007827155,0.0001009134,0.6942331,0.00004187805,0.00009152708,4.298982e-7,0.1220549,0.000005549562,0.002032341,0.1700124,0.01025749,0.0003866922],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930109,0.000407147,0.00003695548,0.00304536,0.001211499,0.0002549557,0.00001064529,0.000132587,0.001889976],"genre_scores_gemma":[0.9976181,0.00002231203,0.0006143833,0.0001825548,0.0009586156,0.00005088648,0.00001319172,0.000008909878,0.0005310833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3596122,"threshold_uncertainty_score":0.5850747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0282299365824669,"score_gpt":0.3182618531287616,"score_spread":0.2900319165462947,"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."}}