{"id":"W4408100312","doi":"10.26599/tst.2024.9010065","title":"Social Media-Driven User Community Finding with Privacy Protection","year":2025,"lang":"en","type":"article","venue":"Tsinghua Science & Technology","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China Postdoctoral Science Foundation","keywords":"Internet privacy; Privacy protection; Computer science; Social media; Computer security; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003547946,0.0006801646,0.001091279,0.002988991,0.001694342,0.00164789,0.002093994,0.00156459,0.0009277632],"category_scores_gemma":[0.01369512,0.0004508695,0.001144681,0.00210628,0.001495844,0.00447258,0.004524773,0.001463651,0.0004458765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001038164,"about_ca_system_score_gemma":0.001789712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002082287,"about_ca_topic_score_gemma":0.002447383,"domain_scores_codex":[0.994389,0.001740868,0.0002469355,0.001130643,0.002051315,0.0004411745],"domain_scores_gemma":[0.9870302,0.00458601,0.00171437,0.004418896,0.00178025,0.0004703294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007335972,0.0006892145,0.02612315,0.0005323029,0.0003004244,0.0007110898,0.00305255,0.1100371,0.07076674,0.1036773,0.005301642,0.678075],"study_design_scores_gemma":[0.00004481146,0.0001977542,0.003717672,0.00004327313,0.0000552356,0.0008449745,0.0009116943,0.8832082,0.03398363,0.06993945,0.00697868,0.00007462892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03471691,0.0001849571,0.9624353,0.0003865153,0.00003100549,0.0002728344,0.0001630935,0.000593977,0.001215417],"genre_scores_gemma":[0.5925782,0.0001364013,0.4044108,0.0001510136,0.00007054051,0.0002442559,0.0003476592,0.00005739259,0.002003831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003547946,"threshold_uncertainty_score":0.0187636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0505621800898568,"score_gpt":0.341973125649909,"score_spread":0.2914109455600522,"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."}}