{"id":"W3014768785","doi":"10.36227/techrxiv.12061662.v1","title":"Identifying Social Media Influencers using Graph Analytics","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Influencer marketing; Social media; Computer science; Social network analysis; Graph; Analytics; Information sharing; Data science; Social network (sociolinguistics); Social media analytics; World Wide Web; Data mining; Theoretical computer science; Business","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001417932,0.0003375669,0.0005927705,0.0002101637,0.000179199,0.0002604383,0.0005344197,0.0001297873,0.0009274458],"category_scores_gemma":[0.000007090508,0.0003611387,0.0006338138,0.0004594276,0.00008648311,0.00007413345,0.001217842,0.0007389956,0.00001570729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007838731,"about_ca_system_score_gemma":0.0001453409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000774679,"about_ca_topic_score_gemma":0.00004263295,"domain_scores_codex":[0.9982558,0.00006416359,0.0004894286,0.0005436426,0.0003438345,0.0003030668],"domain_scores_gemma":[0.9990062,0.00006498871,0.0003552081,0.0003486704,0.0001181193,0.0001067857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007753773,0.0005360029,0.2511013,0.0007488882,0.01423147,0.00006472346,0.01732317,0.04981311,0.007244446,0.4938509,0.07810342,0.08690508],"study_design_scores_gemma":[0.0002578119,0.000006811998,0.003986629,0.0001605912,0.001542092,3.291137e-7,0.001370077,0.09466545,0.00129967,0.8943211,0.00102452,0.001364902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1948715,0.00008853092,0.7873511,0.0002925254,0.0004436836,0.0003617987,0.00009101597,0.0005353359,0.01596444],"genre_scores_gemma":[0.9802709,0.000004624083,0.01777164,0.00006725049,0.001617166,0.00001349553,0.0001914455,0.00003930759,0.00002416248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7853994,"threshold_uncertainty_score":0.9999858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1058032998645926,"score_gpt":0.347804998868497,"score_spread":0.2420016990039043,"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."}}