{"id":"W4389855353","doi":"10.1016/j.dss.2023.114148","title":"Play it safe or leave the comfort zone? Optimal content strategies for social media influencers on streaming video platforms","year":2023,"lang":"en","type":"article","venue":"Decision Support Systems","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Influencer marketing; Variation (astronomy); Computer science; Time horizon; Markov decision process; Advertising; Marketing; Business; Markov process; Marketing management","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":[0.001215806,0.0006135795,0.0003788439,0.0009057377,0.000735015,0.002795276,0.0006813899,0.0008931984,0.00929952],"category_scores_gemma":[0.008763777,0.0002517425,0.0002967867,0.0003708185,0.0005604086,0.002505027,0.0008021489,0.0006305363,0.0008923545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152865,"about_ca_system_score_gemma":0.001898246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006474084,"about_ca_topic_score_gemma":0.01287629,"domain_scores_codex":[0.9993472,0.0002648141,0.00001478309,0.00007798606,0.00008061592,0.0002145759],"domain_scores_gemma":[0.9970806,0.001912114,0.0002455035,0.00006126173,0.0002681483,0.0004323213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005975522,0.007390577,0.1380243,0.0007400359,0.0003525959,0.0009001801,0.008115568,0.07648813,0.03106241,0.05036044,0.007758036,0.6728322],"study_design_scores_gemma":[0.0006922967,0.004340462,0.08915525,0.0003841424,0.0006912734,0.0002150344,0.05960781,0.7261701,0.0205467,0.0877247,0.01030427,0.0001679946],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697075,0.000228876,0.01212095,0.001078691,0.00002790388,0.0002315565,0.00005317471,0.00004933212,0.01650213],"genre_scores_gemma":[0.995768,0.00008024962,0.003050901,0.00003794083,0.000009546583,0.00004066461,0.00001846826,0.0000111718,0.0009832601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00929952,"threshold_uncertainty_score":0.03110999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1403754251632413,"score_gpt":0.3657733569260477,"score_spread":0.2253979317628065,"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."}}