{"id":"W4317387810","doi":"10.18280/mmep.090617","title":"Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Imam Abdulrahman Bin Faisal University; Saudi Aramco","keywords":"Sarcasm; Sentiment analysis; Computer science; Social media; Artificial intelligence; Natural language processing; Arabic; Customer satisfaction; Deep learning; Encoder; Recall; World Wide Web; Linguistics; Business; Marketing","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":[0.0005716197,0.001145321,0.0007245768,0.001362326,0.0006426105,0.00101481,0.0007121758,0.001140284,0.001500003],"category_scores_gemma":[0.001599294,0.000366574,0.0009749728,0.0004147144,0.0003474574,0.0007164119,0.0004319538,0.001071657,0.001416418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001131801,"about_ca_system_score_gemma":0.0007589691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01595143,"about_ca_topic_score_gemma":0.01587921,"domain_scores_codex":[0.999781,0.00004393771,0.00001475242,0.00005745476,0.00004938519,0.00005350001],"domain_scores_gemma":[0.9994202,0.0002294508,0.0000569398,0.0000293271,0.0002365673,0.00002751513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001375211,0.0008735825,0.04658537,0.000251715,0.0004429852,0.001158756,0.0006636795,0.5052527,0.02297021,0.005048196,0.02185711,0.3935204],"study_design_scores_gemma":[0.00000460224,0.00002239705,0.0008899572,0.000006597593,0.00001595189,0.00002826401,0.00002044025,0.9964489,0.001590585,0.000430984,0.0005349229,0.000006318932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7440373,0.003010325,0.2206153,0.003812745,0.0009329902,0.0003483212,0.00188997,0.007130612,0.0182224],"genre_scores_gemma":[0.9535164,0.0005562588,0.03190457,0.0004843973,0.000230484,0.0001041121,0.001614435,0.0001081965,0.01148112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01595143,"threshold_uncertainty_score":0.03171718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03150540110276414,"score_gpt":0.2207928954795215,"score_spread":0.1892874943767573,"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."}}