{"id":"W4319599375","doi":"10.3390/computers12020037","title":"Artificial Intelligence and Sentiment Analysis: A Review in Competitive Research","year":2023,"lang":"en","type":"review","venue":"Computers","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":195,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"Competitor analysis; Sentiment analysis; Competitive intelligence; Connotation; Competition (biology); Process (computing); Statement (logic); Marketing; Computer science; Data science; Business; Artificial intelligence; Political science; Linguistics","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":[0.00201039,0.000945847,0.00159089,0.004615501,0.0004603219,0.002090238,0.0008376094,0.001659731,0.003674479],"category_scores_gemma":[0.003242322,0.0004384487,0.001117658,0.007516744,0.0009940042,0.002663003,0.0007452428,0.001736654,0.001807933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009493703,"about_ca_system_score_gemma":0.001646819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001745564,"about_ca_topic_score_gemma":0.002779253,"domain_scores_codex":[0.9993275,0.0001831353,0.0001243587,0.00009220891,0.0002391804,0.00003352905],"domain_scores_gemma":[0.996739,0.002292906,0.0002342623,0.00004424027,0.0006076306,0.00008188291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006003728,0.00006790514,0.0003930738,0.03538179,0.0001749151,0.0001455645,0.000162617,0.0002418492,0.0005744316,0.004727435,0.03670321,0.9213671],"study_design_scores_gemma":[0.00002402616,0.0001120416,0.00217419,0.02118555,0.0003383151,0.0007445823,0.0002397909,0.0002471624,0.0003169934,0.005470377,0.9690962,0.00005079126],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007705561,0.9981273,0.000159283,0.0004949119,0.0002270837,0.000007648809,0.00001290089,0.000004693488,0.0008891422],"genre_scores_gemma":[0.0005815459,0.9983547,0.0002882653,0.0002745641,0.0002700026,0.000009165817,0.00001918585,0.000002004087,0.0002005452],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004615501,"threshold_uncertainty_score":0.01229233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3576481061405088,"score_gpt":0.5144941713526183,"score_spread":0.1568460652121095,"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."}}