{"id":"W4392344560","doi":"10.18280/isi.290138","title":"Sentiment Analysis Methods for Arabic Content on Social Media: A Systematic Review","year":2024,"lang":"fr","type":"review","venue":"Ingénierie des systèmes d information","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Qassim University","keywords":"Sentiment analysis; Lexicon; Computer science; Variety (cybernetics); Natural language processing; Pronunciation; Linguistics; Artificial intelligence; Grammar; Syntax; Social media; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007260197,0.00109877,0.00581278,0.001999032,0.000679078,0.002099979,0.001293088,0.0004736357,0.0001556078],"category_scores_gemma":[0.001997685,0.0008411487,0.004662886,0.005221638,0.0001708046,0.002258517,0.0003679782,0.00050373,0.001416108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001402534,"about_ca_system_score_gemma":0.0003713552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001964667,"about_ca_topic_score_gemma":0.000005554482,"domain_scores_codex":[0.9905765,0.001604818,0.005154331,0.000781324,0.001058137,0.0008248864],"domain_scores_gemma":[0.9923657,0.001653655,0.0035967,0.001043208,0.001103361,0.0002373376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000003924791,0.00004217115,5.799274e-7,0.7111816,0.006872463,0.000002685947,0.003723041,0.00002227783,2.527428e-7,0.01733511,0.002061888,0.258754],"study_design_scores_gemma":[0.0003475014,0.0001380987,0.000009120659,0.7178881,0.09773823,0.000044497,0.0007056898,0.07780869,0.00001015133,0.0008531096,0.1031256,0.001331253],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001538946,0.6471806,0.3469316,0.0002763781,0.001815701,0.003164062,0.00009756364,0.0001289597,0.0004036795],"genre_scores_gemma":[0.00008461328,0.9646834,0.0279934,0.001007423,0.0004544177,0.003079652,0.00171124,0.0000609273,0.0009249736],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3189382,"threshold_uncertainty_score":0.999404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1415636493640359,"score_gpt":0.3844589842958041,"score_spread":0.2428953349317682,"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."}}