{"id":"W4415266424","doi":"10.1080/1369118x.2025.2561046","title":"Hijacking algorithmic bias: analyzing the political discourse around ChatGPT on social media","year":2025,"lang":"en","type":"article","venue":"Information Communication & Society","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation; Tel Aviv University","keywords":"Politics; Social media; Discourse analysis; Political communication; The Internet","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01687673,0.0004228887,0.0004162643,0.002388613,0.00506962,0.006950316,0.0008354266,0.001437104,0.001728834],"category_scores_gemma":[0.04332123,0.0003529307,0.0002320957,0.00186825,0.01427593,0.007614645,0.005159391,0.002182737,0.0002910866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002576011,"about_ca_system_score_gemma":0.001388111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00222048,"about_ca_topic_score_gemma":0.003069814,"domain_scores_codex":[0.9846577,0.01221012,0.0003158793,0.0006774533,0.001647797,0.0004910486],"domain_scores_gemma":[0.9185372,0.07266729,0.003125639,0.003044011,0.00192724,0.0006986005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001244251,0.00002846044,0.008835576,0.000156813,0.0000128621,0.0003793415,0.9587343,0.0001573658,0.00433969,0.01321653,0.0005010542,0.01351362],"study_design_scores_gemma":[0.00003874602,0.0002425623,0.02392582,0.0006125307,0.00003716055,0.0005836278,0.8887783,0.002582738,0.007191997,0.01461933,0.06129063,0.0000966008],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813695,0.0003003672,0.005436196,0.001253825,0.00003954675,0.00005791979,0.00004441347,0.00004586322,0.01145249],"genre_scores_gemma":[0.9977371,0.000125951,0.0009799768,0.0001971945,0.00002676373,0.00005353075,0.0000259168,0.0000377577,0.0008159102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9949304,"threshold_uncertainty_score":0.08925372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08769697233848028,"score_gpt":0.4094169909077949,"score_spread":0.3217200185693146,"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."}}