{"id":"W2276717191","doi":"10.1002/cpe.3773","title":"Parallel social network mining for interesting ‘following’ patterns","year":2016,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Interdependence; Computer science; Friendship; Social network (sociolinguistics); Social network analysis; Data science; Data mining; World Wide Web; Social media; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001179324,0.0006236875,0.001014503,0.004357516,0.001205489,0.001388701,0.001778234,0.0008053427,0.00203845],"category_scores_gemma":[0.008978977,0.0004497328,0.001191555,0.004186015,0.0006059856,0.002194315,0.001567183,0.0008240564,0.000881683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006782222,"about_ca_system_score_gemma":0.001298472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003774341,"about_ca_topic_score_gemma":0.006253236,"domain_scores_codex":[0.9979826,0.0003043104,0.0002283402,0.0005948474,0.0007071624,0.0001826957],"domain_scores_gemma":[0.9954785,0.001627872,0.0007527393,0.001115994,0.0008331076,0.000191927],"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":[0.001028198,0.000919376,0.1125104,0.0005406251,0.0006061203,0.001423171,0.001098724,0.1957282,0.01836389,0.0344995,0.0176267,0.6156551],"study_design_scores_gemma":[0.00003089313,0.00006478372,0.005623571,0.00001899839,0.0000508466,0.0003863754,0.000218814,0.9535578,0.005016325,0.02993098,0.005082698,0.00001790371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3954404,0.0006159044,0.5883375,0.001269722,0.000118026,0.0004880161,0.005055825,0.002933567,0.005740975],"genre_scores_gemma":[0.7031862,0.0001362004,0.2883624,0.00007962187,0.00005850776,0.0002168936,0.005938976,0.00009081871,0.001930373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004357516,"threshold_uncertainty_score":0.007504761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0467482113840547,"score_gpt":0.3547713504565648,"score_spread":0.3080231390725101,"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."}}