{"id":"W131176858","doi":"","title":"The Utility of Using Social Media Networks for Data Collection in Survey Research","year":2013,"lang":"en","type":"article","venue":"International Conference on Information Systems","topic":"Social Media and Politics","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; University of Ottawa; McGill University","funders":"","keywords":"Computer science; Data collection; Social media; Data science; World Wide Web; Statistics; Mathematics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2560558,0.001336662,0.001408877,0.01077722,0.003360657,0.007784517,0.003676688,0.003625316,0.005738479],"category_scores_gemma":[0.6685334,0.002052856,0.001929298,0.0166111,0.00384917,0.01351607,0.005351285,0.003208216,0.001530344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003557316,"about_ca_system_score_gemma":0.005277633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009736812,"about_ca_topic_score_gemma":0.017736,"domain_scores_codex":[0.4996119,0.4656051,0.01081503,0.006031247,0.01684152,0.001095258],"domain_scores_gemma":[0.08582818,0.8416238,0.0132843,0.03724242,0.02091559,0.001105647],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001428257,0.0009403701,0.5365601,0.004134416,0.002809482,0.0003752268,0.01575329,0.009737724,0.001318145,0.04446953,0.0161358,0.3663377],"study_design_scores_gemma":[0.0007544123,0.003072296,0.4628923,0.004419919,0.003104178,0.001593379,0.02407099,0.1712613,0.01051715,0.2140995,0.1033524,0.0008623566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2685709,0.008089301,0.6190612,0.01485208,0.00131306,0.008940119,0.008019441,0.000903299,0.07025056],"genre_scores_gemma":[0.7354728,0.002331625,0.2458546,0.001532717,0.0006540652,0.009282779,0.001638011,0.0002268639,0.003006503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7439442,"threshold_uncertainty_score":0.9174157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5188045478667734,"score_gpt":0.4914853979933276,"score_spread":0.02731914987344586,"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."}}