{"id":"W3217030887","doi":"10.18280/isi.260510","title":"A Proportional Sentiment Analysis of MOOCs Course Reviews Using Supervised Learning Algorithms","year":2021,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Computer science; Bigram; Naive Bayes classifier; Artificial intelligence; Machine learning; Support vector machine; Sentence; Supervised learning; Perceptron; Natural language processing; Online learning; Term (time); Margin (machine learning); Artificial neural network; Trigram; 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":[],"consensus_categories":[],"category_scores_codex":[0.0007050313,0.0001299373,0.0003704369,0.0003113871,0.0001854235,0.0002023292,0.0002205489,0.00006109932,0.00003678437],"category_scores_gemma":[0.0002293696,0.0001238732,0.0002175369,0.002011766,0.00005113108,0.001501692,0.0001213277,0.000148906,0.00001970593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001117679,"about_ca_system_score_gemma":0.0002313975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003132467,"about_ca_topic_score_gemma":0.000002898696,"domain_scores_codex":[0.9983265,0.0001465506,0.0007829057,0.0001521425,0.0003909108,0.0002010193],"domain_scores_gemma":[0.9985205,0.00003560379,0.0005396678,0.0002987221,0.0005404504,0.00006508463],"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":[0.00001245294,0.0003314144,0.06584069,0.0009670497,0.001855199,0.00002977189,0.01693043,0.446494,0.002204765,0.01233363,0.0001872723,0.4528134],"study_design_scores_gemma":[0.0001522579,0.00002904339,0.004734239,0.0001224867,0.000277068,0.0000178369,0.0004947924,0.9914855,0.0007103634,0.0002711988,0.001561001,0.0001442116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2148081,0.0004850238,0.7836713,0.0001628,0.0001396159,0.0001347772,0.000007855489,0.00009775534,0.000492743],"genre_scores_gemma":[0.8838008,0.0001082539,0.1155606,0.0001061365,0.00004388514,0.000007859292,0.0002020092,0.00000618139,0.0001643068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6689926,"threshold_uncertainty_score":0.5051401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02590904730291073,"score_gpt":0.2891098331423615,"score_spread":0.2632007858394508,"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."}}