{"id":"W4394912621","doi":"10.5267/j.ijdns.2024.3.006","title":"Sentiment analysis of Saudi e-commerce using naïve bayes algorithm and support vector machine","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"AstraZeneca","keywords":"Naive Bayes classifier; Support vector machine; Bayes' theorem; Computer science; Sentiment analysis; Artificial intelligence; Algorithm; Machine learning; Data mining; Bayesian probability","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":[],"consensus_categories":[],"category_scores_codex":[0.001646508,0.00008626287,0.000226884,0.0006169486,0.00008894361,0.0005020359,0.001450686,0.00001722911,0.00004421362],"category_scores_gemma":[0.00002565459,0.00006720392,0.00007228202,0.001318418,0.0001581953,0.001667237,0.0009223997,0.00009513617,6.88455e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002939487,"about_ca_system_score_gemma":0.0001154334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001981728,"about_ca_topic_score_gemma":0.000003426171,"domain_scores_codex":[0.9983042,0.00003082268,0.0004276168,0.0003079642,0.000782209,0.0001471224],"domain_scores_gemma":[0.9990463,0.0001333937,0.000252934,0.0002522815,0.0002191591,0.00009595355],"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":[0.00002741673,0.0001475062,0.04551542,0.00002230225,0.004997033,0.0002187867,0.001624516,0.006750593,0.004368722,0.009436407,0.002931866,0.9239594],"study_design_scores_gemma":[0.0001011445,0.00003884849,0.00816457,0.00007961251,0.0002450967,0.00008799589,0.0000296067,0.9886893,0.0002112675,0.0001493842,0.002129141,0.00007402949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06513654,0.003943562,0.9280868,0.001087581,0.001532374,0.00003722525,0.00007398322,0.00001104364,0.00009087054],"genre_scores_gemma":[0.8594999,0.0007719803,0.1392144,0.0001487823,0.0002970916,1.738446e-7,0.00002143598,0.000003919608,0.00004235308],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9819387,"threshold_uncertainty_score":0.4841144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0367909685756815,"score_gpt":0.3493871229390602,"score_spread":0.3125961543633787,"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."}}