{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001308408,0.0002781686,0.0002470421,0.0007014628,0.0003452984,0.002182093,0.000292561,0.0002261793,0.00001995555],"category_scores_gemma":[0.0003221286,0.0003087219,0.000162453,0.0009468197,0.0001035789,0.008891181,0.00009515516,0.0005278432,0.0001773119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007850668,"about_ca_system_score_gemma":0.0001112318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004245736,"about_ca_topic_score_gemma":0.00003177901,"domain_scores_codex":[0.9979411,0.000156784,0.0007240561,0.0003384165,0.0002981305,0.0005414879],"domain_scores_gemma":[0.9990993,0.0001665121,0.0001903618,0.0002458811,0.0002057702,0.00009220087],"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":[0.00004442459,0.00002863492,0.0001174199,0.002276967,0.00003932883,0.000006937327,0.02133129,0.02377403,0.0001889099,0.005460686,0.0003138971,0.9464175],"study_design_scores_gemma":[0.0003336833,0.0002611736,0.0005915246,0.000475635,0.00002634206,0.0002676063,0.000388396,0.9347248,0.002569263,0.009176017,0.05084932,0.0003362557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03478721,0.002938987,0.9509408,0.0001992538,0.004508954,0.0006838816,0.000006981182,0.0004368988,0.005496995],"genre_scores_gemma":[0.9848208,0.0001063319,0.01325474,0.0001450129,0.0005135099,0.0002626239,0.00006973578,0.00002598255,0.0008012588],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9500336,"threshold_uncertainty_score":0.9999365,"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."}}