{"id":"W4236542667","doi":"10.4018/978-1-7998-0414-7.ch077","title":"Sentiment Recognition in Customer Reviews Using Deep Learning","year":2019,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Deep learning; Artificial intelligence; Sentiment analysis; Computer science; Machine learning; Artificial neural network; Support vector machine; Convolutional neural network; Natural language processing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003829476,0.0006076423,0.0004286892,0.0006778887,0.0001495468,0.0008224369,0.0003104412,0.0004001614,0.002530803],"category_scores_gemma":[0.0009443262,0.0001972245,0.000505372,0.000673852,0.0001191835,0.0006591399,0.0003308368,0.0006490664,0.002246692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003847982,"about_ca_system_score_gemma":0.0002388959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00181911,"about_ca_topic_score_gemma":0.003297369,"domain_scores_codex":[0.9997862,0.00004487561,0.00001455669,0.00004279734,0.0000801673,0.00003142443],"domain_scores_gemma":[0.9996403,0.00009643316,0.00005471781,0.00001959227,0.0001737665,0.00001521705],"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":[0.0002915769,0.0002113432,0.008450187,0.0005052116,0.0001526693,0.0002758247,0.0002197655,0.01906268,0.06196853,0.002235236,0.02501707,0.88161],"study_design_scores_gemma":[0.00001591565,0.0001406002,0.0116369,0.00008634976,0.00007593194,0.0002091735,0.0001737529,0.9422581,0.02891217,0.004286691,0.01217233,0.00003205015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3300649,0.006580797,0.612973,0.002236602,0.0008387576,0.0003217761,0.00345144,0.005674379,0.03785836],"genre_scores_gemma":[0.8037301,0.002915204,0.1689672,0.0005056201,0.0002954529,0.000117076,0.003426269,0.0001531718,0.01988994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002530803,"threshold_uncertainty_score":0.008466423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05057857399141688,"score_gpt":0.2861576284545343,"score_spread":0.2355790544631174,"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."}}