{"id":"W1600928385","doi":"10.1609/icwsm.v2i1.18624","title":"A Social Network Based Approach to Personalized Recommendation of Participatory Media Content","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International AAAI Conference on Web and Social Media","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Recommender system; Computer science; Citizen journalism; Bayesian network; Set (abstract data type); Social media; Preference; Diversity (politics); Personalization; World Wide Web; Social network (sociolinguistics); Content (measure theory); Information retrieval; Data science; Artificial intelligence; Sociology","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":[0.00249222,0.0008621307,0.001061814,0.002767795,0.001607908,0.002150015,0.002255377,0.001819873,0.005146316],"category_scores_gemma":[0.009002455,0.0007110311,0.001413668,0.002857149,0.001070468,0.003878081,0.001546146,0.001525078,0.001245938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001859341,"about_ca_system_score_gemma":0.00131973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01636689,"about_ca_topic_score_gemma":0.03076433,"domain_scores_codex":[0.996781,0.001509013,0.0001222346,0.0006721668,0.0007814646,0.0001339877],"domain_scores_gemma":[0.9961415,0.002378781,0.00028655,0.000438139,0.0005868194,0.0001681467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00032045,0.0005112051,0.006788092,0.0006047304,0.000583974,0.0005702151,0.001903696,0.5006792,0.006426147,0.2574905,0.007546516,0.2165752],"study_design_scores_gemma":[0.00002804576,0.0001007209,0.0008631978,0.00003527115,0.0000788684,0.0001434706,0.000123756,0.9409672,0.0005890789,0.0492619,0.007764515,0.00004392259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.011485,0.0004855859,0.9771255,0.0009088786,0.00008926028,0.0001968315,0.0001796066,0.0002597976,0.009269504],"genre_scores_gemma":[0.5234334,0.001110157,0.4530896,0.0002941798,0.0003306624,0.0005417723,0.0003562247,0.0001012634,0.0207428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01636689,"threshold_uncertainty_score":0.03254324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1593367662843782,"score_gpt":0.3022923984066367,"score_spread":0.1429556321222586,"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."}}