{"id":"W2968073071","doi":"10.1016/j.chb.2019.08.006","title":"Hashtag homophily in twitter network: Examining a controversial cause-related marketing campaign","year":2019,"lang":"en","type":"article","venue":"Computers in Human Behavior","topic":"Social Media and Politics","field":"Social Sciences","cited_by":85,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Centre de Recherches Mathématiques","keywords":"Homophily; Ideology; Exponential random graph models; Social media; Social network (sociolinguistics); Influencer marketing; Advertising; Social network analysis; Social psychology; Sociology; Psychology; Computer science; Graph; Political science; Politics; World Wide Web; Random graph; Marketing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009485841,0.0001638351,0.0003264598,0.0001589667,0.0002404664,0.0000924038,0.0003427078,0.0002378941,0.0002807674],"category_scores_gemma":[0.00009420991,0.0001957993,0.00006770241,0.0003673756,0.0002185358,0.0001438922,0.00009325534,0.0004119257,0.00005141951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003470485,"about_ca_system_score_gemma":0.0001126578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001330855,"about_ca_topic_score_gemma":0.0009211834,"domain_scores_codex":[0.9975994,0.000619263,0.0003975675,0.0003169727,0.0003086457,0.0007581188],"domain_scores_gemma":[0.9988143,0.0007038313,0.0001228335,0.0001907361,0.00003767528,0.0001305879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001359558,0.0000717568,0.9584199,0.000007872053,0.00000802451,0.0001102467,0.03719717,0.00005236694,0.00009339516,0.00155972,0.00111406,0.00135189],"study_design_scores_gemma":[0.002716865,0.0001106627,0.9765339,0.0003477414,0.00005053606,0.000002679344,0.01599159,0.0001774989,0.000006134173,0.0006926971,0.002837467,0.0005322557],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925241,0.00005324707,0.00001063944,0.0001128486,0.003067988,0.0006201902,0.000002115756,0.00007780203,0.003531092],"genre_scores_gemma":[0.9982601,0.000006166836,0.0002468548,0.0002965498,0.0007124339,0.00003617425,0.000009692277,0.00002324012,0.0004087633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02120557,"threshold_uncertainty_score":0.7984465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04998510692510898,"score_gpt":0.3260278857117636,"score_spread":0.2760427787866546,"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."}}