{"id":"W3147773549","doi":"10.18280/ria.350107","title":"Research on Text Sentiment Analysis Based on Neural Network and Ensemble Learning","year":2021,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Educational Technology and Pedagogy","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wuhan Institute of Technology; National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Artificial intelligence; Sentiment analysis; Convolutional neural network; Preprocessor; Artificial neural network; Support vector machine; Vectorization (mathematics); Word (group theory); Ensemble learning; Data pre-processing; Machine learning; Pattern recognition (psychology); Natural language processing","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":[0.001497314,0.00105814,0.00124934,0.002280799,0.0004677086,0.001284476,0.0008777358,0.0007410845,0.001131087],"category_scores_gemma":[0.003060027,0.0003096505,0.001363332,0.002446381,0.0003544568,0.003446723,0.0004914093,0.001038336,0.0004562872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00061022,"about_ca_system_score_gemma":0.0004587882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307653,"about_ca_topic_score_gemma":0.00170204,"domain_scores_codex":[0.9989982,0.0001863548,0.00008205051,0.0003069674,0.0003513021,0.00007506063],"domain_scores_gemma":[0.9987277,0.0004552093,0.0001322768,0.0001121836,0.00053365,0.00003896784],"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":[0.0001304194,0.0001769504,0.009874681,0.0004130919,0.0005684817,0.0001223199,0.0002428632,0.06004321,0.01414024,0.01293177,0.004888314,0.8964677],"study_design_scores_gemma":[0.000012183,0.0001137594,0.005309764,0.00005143564,0.0002020554,0.0001203711,0.00009858418,0.9671116,0.00716038,0.0132576,0.006521317,0.00004092095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05553377,0.007975772,0.927265,0.0008058372,0.0005637474,0.0001001415,0.0001910355,0.0008139253,0.006750697],"genre_scores_gemma":[0.7108554,0.01248814,0.2664538,0.0004042694,0.001538842,0.0002372753,0.001012231,0.0002001686,0.006809946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002307653,"threshold_uncertainty_score":0.007918656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1073994801737365,"score_gpt":0.3803853914787971,"score_spread":0.2729859113050606,"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."}}