{"id":"W4385078483","doi":"10.18280/isi.280325","title":"An Innovative Arabic Word Embedding Representation for Enhanced Sentiment Analysis","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arabic; Natural language processing; Representation (politics); Word (group theory); Word embedding; Sentiment analysis; Computer science; Embedding; Artificial intelligence; Linguistics; Political science; Philosophy","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":[0.00035597,0.0008010546,0.0004171979,0.00101428,0.0002478749,0.0008354385,0.000341053,0.0004225669,0.003716041],"category_scores_gemma":[0.001658165,0.00012796,0.0004952895,0.001036247,0.0002196792,0.001295273,0.0006958771,0.0005890732,0.002360405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001814185,"about_ca_system_score_gemma":0.0003359087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006948768,"about_ca_topic_score_gemma":0.0009733866,"domain_scores_codex":[0.9997274,0.00006968779,0.00002983457,0.00005987319,0.00008163599,0.00003161511],"domain_scores_gemma":[0.9996124,0.0001080125,0.00004402568,0.00003892956,0.0001798041,0.00001684817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003374591,0.0001097595,0.001062827,0.0002295283,0.00005369302,0.000185048,0.0002820464,0.009967909,0.07929602,0.00889813,0.008852605,0.890725],"study_design_scores_gemma":[0.0000575377,0.0004761644,0.003375059,0.000102065,0.0001275739,0.000784458,0.0005868893,0.8578573,0.07145154,0.01779614,0.04729801,0.0000871408],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0617922,0.0008595733,0.9283668,0.0004781683,0.0004742157,0.0001540245,0.000802391,0.002417305,0.004655395],"genre_scores_gemma":[0.3695706,0.001176269,0.6169106,0.0002566002,0.0002886011,0.0002646162,0.002533411,0.0003339713,0.008665238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003716041,"threshold_uncertainty_score":0.01243144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02826391856671492,"score_gpt":0.3187361640530686,"score_spread":0.2904722454863538,"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."}}