{"id":"W4410049912","doi":"10.1145/3710970","title":"Exploring Algorithmic Resistance: Responses to Social Media Censorship in Activism","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Universitas Brawijaya; Bundesministerium für Bildung und Forschung","keywords":"Censorship; Social media; Political science; Mores; Public relations; Sociology; Politics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009462981,0.0005073763,0.0003495326,0.002164428,0.005378919,0.009218124,0.001307732,0.002853742,0.004651722],"category_scores_gemma":[0.04058734,0.0003824211,0.0004258418,0.001353725,0.01176071,0.006674338,0.007753259,0.003385559,0.0004971948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002343324,"about_ca_system_score_gemma":0.00107804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001675844,"about_ca_topic_score_gemma":0.002112683,"domain_scores_codex":[0.9854695,0.01095361,0.000318932,0.001029912,0.001271884,0.0009561343],"domain_scores_gemma":[0.9446077,0.04424587,0.006346611,0.002131724,0.001651264,0.001016819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001768669,0.0001354493,0.02879145,0.0002128228,0.00004549518,0.0007003886,0.9174694,0.000289724,0.003075893,0.02243655,0.001083284,0.02558258],"study_design_scores_gemma":[0.00003709941,0.0001894412,0.04246445,0.0003840488,0.00004751458,0.0005355769,0.8926309,0.001898671,0.001899274,0.02013696,0.03971286,0.00006317458],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9398636,0.0002878416,0.005066619,0.00420668,0.00007186391,0.0001000957,0.00005775594,0.00004620965,0.05029933],"genre_scores_gemma":[0.9973179,0.00009486125,0.0006170183,0.0004081177,0.00002957606,0.00007010337,0.00002085752,0.00002384151,0.001417702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009462981,"threshold_uncertainty_score":0.05004561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1239332525760814,"score_gpt":0.3295972512505024,"score_spread":0.205663998674421,"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."}}