{"id":"W3007466464","doi":"10.1007/s11280-020-00785-z","title":"A comprehensive analysis of adverb types for mining user sentiments on amazon product reviews","year":2020,"lang":"en","type":"article","venue":"World Wide Web","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Adverb; Sentiment analysis; Superlative; Computer science; Natural language processing; Degree (music); Artificial intelligence; Product (mathematics); Meaning (existential); Linguistics; Information retrieval; Noun; Mathematics; Psychology","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":[0.0007817094,0.0005797161,0.0006145015,0.003712149,0.0005130632,0.0009478773,0.000310884,0.0003364497,0.00110705],"category_scores_gemma":[0.003095119,0.0002134459,0.001012678,0.003231065,0.000117741,0.001227757,0.0004194131,0.0004133882,0.0008741474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003457985,"about_ca_system_score_gemma":0.0007966905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005817,"about_ca_topic_score_gemma":0.0146111,"domain_scores_codex":[0.9991096,0.0001436209,0.0001009377,0.0001266908,0.0004552841,0.00006387808],"domain_scores_gemma":[0.9983056,0.0005821681,0.0001871239,0.0001356649,0.000695832,0.00009369155],"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":[0.0008302009,0.0007230596,0.1567825,0.001784578,0.0008981104,0.001222346,0.0006296434,0.003422749,0.09658841,0.002465156,0.03412193,0.7005313],"study_design_scores_gemma":[0.0000960055,0.0008976335,0.607792,0.0002611047,0.001303134,0.002212433,0.001434227,0.3052136,0.03539782,0.003445874,0.04178447,0.0001616785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9002478,0.006845478,0.0633941,0.000589491,0.0001868287,0.000490263,0.01710243,0.00219047,0.008953233],"genre_scores_gemma":[0.888745,0.001853292,0.08164468,0.0001547123,0.0002085856,0.0002577074,0.02274938,0.0001332717,0.004253485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005817,"threshold_uncertainty_score":0.01156628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05783494863255713,"score_gpt":0.3031553894291836,"score_spread":0.2453204407966265,"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."}}