{"id":"W4410416953","doi":"10.54254/2753-8818/2025.22733","title":"Sentiment Analysis Applied on Tweets","year":2025,"lang":"en","type":"article","venue":"Theoretical and Natural Science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sentiment analysis; Computer science; Information retrieval; Data science; Natural language processing; World Wide Web","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":[0.001078076,0.0006417001,0.0003798286,0.002432267,0.0005502761,0.001432567,0.000275579,0.0003415426,0.004571259],"category_scores_gemma":[0.005503997,0.0001338311,0.0008465552,0.002024138,0.0002301025,0.001046528,0.0004845504,0.0006677993,0.002412117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006028317,"about_ca_system_score_gemma":0.0005621306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002805606,"about_ca_topic_score_gemma":0.002597889,"domain_scores_codex":[0.9991333,0.0002297341,0.0001039606,0.0001572988,0.0002758061,0.0000998334],"domain_scores_gemma":[0.9984283,0.0005799477,0.0001418645,0.0001024705,0.000709709,0.00003764198],"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":[0.001049898,0.0003258122,0.05432946,0.001282453,0.0004731592,0.0007752041,0.002782015,0.02413827,0.09424472,0.01272338,0.02986559,0.7780101],"study_design_scores_gemma":[0.00007396784,0.0005922173,0.09750513,0.0003399787,0.0002575724,0.0006312468,0.004585811,0.7098166,0.08200064,0.02179696,0.08224385,0.0001560168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5535101,0.0009926499,0.3661657,0.001515786,0.001469974,0.001738591,0.02099572,0.004162224,0.04944927],"genre_scores_gemma":[0.8545292,0.0005793842,0.1250136,0.000175723,0.0003043422,0.0007234109,0.009938477,0.00024074,0.008495056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004571259,"threshold_uncertainty_score":0.01529241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003777605526262453,"score_gpt":0.2581465589642757,"score_spread":0.2543689534380132,"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."}}