{"id":"W4386834384","doi":"10.18280/ria.370426","title":"Predicting User Engagement of Facebook Post Images in Leading Universities: A Machine Learning Approach","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"User engagement; Computer science; Social media; Human–computer interaction; Data science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001199261,0.0006486619,0.0004638046,0.002993444,0.0003471109,0.001321323,0.0004051673,0.0009075674,0.001400103],"category_scores_gemma":[0.005495656,0.0001492611,0.0005192727,0.001710332,0.0002629724,0.001191376,0.0006002397,0.0007449924,0.001326596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00053692,"about_ca_system_score_gemma":0.000354073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00411844,"about_ca_topic_score_gemma":0.007482383,"domain_scores_codex":[0.999261,0.0003127174,0.00004892105,0.0001225722,0.0001460166,0.0001087142],"domain_scores_gemma":[0.9966288,0.002311273,0.0003821459,0.0001562489,0.0003563908,0.0001650634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006931039,0.001450821,0.6346045,0.0003237572,0.0001751564,0.0002894884,0.001188149,0.0483906,0.005083225,0.0009796378,0.005787147,0.3010345],"study_design_scores_gemma":[0.00001225432,0.0003245228,0.1950153,0.00007196556,0.00004960732,0.0002017629,0.001482454,0.7939606,0.003818404,0.001554798,0.003464381,0.00004402163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740356,0.0005023626,0.01847833,0.0005130076,0.00004335276,0.0001229501,0.001762497,0.0004221916,0.004119848],"genre_scores_gemma":[0.9866485,0.0001251389,0.01065352,0.00003898228,0.00004119486,0.00005976522,0.001352564,0.00001115759,0.001069281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00411844,"threshold_uncertainty_score":0.008188963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04747406391470723,"score_gpt":0.3017143672873809,"score_spread":0.2542403033726737,"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."}}