{"id":"W4392200481","doi":"10.18280/isi.290113","title":"A Hybrid Deep Learning Approach for Spam Detection in Twitter","year":2024,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Deep learning; Artificial intelligence; Spambot; Spamming; Machine learning; World Wide Web; The Internet","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":[0.0003563479,0.0009350427,0.0005694111,0.001492825,0.0004341551,0.0005493708,0.0008999457,0.0008784943,0.00128248],"category_scores_gemma":[0.0008813201,0.0003444748,0.0005762955,0.0009435388,0.0003247973,0.001228519,0.0007720477,0.0006609751,0.0007003773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007312141,"about_ca_system_score_gemma":0.0007748751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007746009,"about_ca_topic_score_gemma":0.008225895,"domain_scores_codex":[0.9997246,0.00004340172,0.00001397542,0.00006395893,0.00007911352,0.00007492589],"domain_scores_gemma":[0.9997782,0.00004309623,0.00003146844,0.00002135185,0.0001055349,0.00002044153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007347813,0.0005685528,0.01522207,0.0001925146,0.0002193777,0.0004480857,0.0001727443,0.1865748,0.02865584,0.004009746,0.01331083,0.7498906],"study_design_scores_gemma":[0.000004471157,0.00003040248,0.000627082,0.000004098643,0.00001362882,0.00002445859,0.00001324836,0.9947982,0.00312636,0.0007178633,0.0006342055,0.000005954523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.206104,0.001657141,0.7759615,0.001178849,0.0002371873,0.0001895395,0.0006713481,0.007299698,0.00670073],"genre_scores_gemma":[0.8859026,0.0006681297,0.1010181,0.0004055935,0.0001672585,0.0001356269,0.001116477,0.0001104309,0.01047581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007746009,"threshold_uncertainty_score":0.01540184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02234628706005385,"score_gpt":0.2377265998864409,"score_spread":0.2153803128263871,"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."}}