{"id":"W4406800538","doi":"10.18280/isi.300109","title":"Travel Vlog Reviews: Support Vector Machine Performance in Sentiment Classification","year":2025,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Katolik Indonesia Atma Jaya; Universitas Indonesia","keywords":"Support vector machine; Computer science; Sentiment analysis; Artificial intelligence; Machine learning; Data mining; Information retrieval","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":[0.003326117,0.0007210576,0.0006506636,0.001252438,0.000340283,0.00128547,0.0004387301,0.0006800946,0.001397259],"category_scores_gemma":[0.01268951,0.0001462415,0.0002745345,0.001250745,0.0001842277,0.001188823,0.0004337142,0.0007946297,0.0009444652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000503976,"about_ca_system_score_gemma":0.0004557273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004308833,"about_ca_topic_score_gemma":0.003368607,"domain_scores_codex":[0.9981725,0.0008046569,0.0001160363,0.0002135038,0.0005851833,0.0001080734],"domain_scores_gemma":[0.9954947,0.002571506,0.0003342092,0.0002934657,0.00118463,0.0001215238],"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":[0.001553715,0.0004548397,0.0363664,0.0003199852,0.0001983323,0.0001235488,0.000223505,0.1133771,0.01213569,0.002026973,0.01654167,0.8166782],"study_design_scores_gemma":[0.00001626122,0.0002340731,0.00434351,0.00001651297,0.00001309209,0.000035906,0.00006816348,0.9890829,0.0041674,0.0006943395,0.001316579,0.00001124601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8665702,0.003566895,0.1094194,0.001653168,0.0004725131,0.0001610309,0.001120668,0.002672692,0.01436347],"genre_scores_gemma":[0.9661223,0.0002782473,0.03130995,0.00006543802,0.00006433815,0.00002691121,0.0007727153,0.00004570258,0.001314297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004308833,"threshold_uncertainty_score":0.0175904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369826723897463,"score_gpt":0.2651353012611111,"score_spread":0.2414370340221365,"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."}}