{"id":"W4401632311","doi":"10.22215/etd/2023-16105","title":"Location-Based Sentiment Analysis using Bayesian Networks on COVID-19 Twitter Data","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Microblogging; Sentiment analysis; Coronavirus disease 2019 (COVID-19); Social media; Naive Bayes classifier; Pandemic; Bayesian probability; Computer science; Classifier (UML); World Wide Web; Data science; Information retrieval; Artificial intelligence; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001602945,0.0007593242,0.0006059975,0.001940067,0.0005743919,0.001070538,0.0005957175,0.000659653,0.001621775],"category_scores_gemma":[0.005188689,0.0002924713,0.0008419072,0.001228593,0.0002656603,0.001198663,0.0006618608,0.001044406,0.001316532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170479,"about_ca_system_score_gemma":0.0005813515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02829658,"about_ca_topic_score_gemma":0.03981109,"domain_scores_codex":[0.9990253,0.0003642539,0.00007679723,0.0002361457,0.0001765515,0.000120991],"domain_scores_gemma":[0.9982684,0.0009861342,0.0002343771,0.00008754392,0.0003405813,0.000082961],"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":[0.001361958,0.0006017201,0.2460054,0.0004367773,0.0005163017,0.001047607,0.001551501,0.281368,0.009570033,0.008502458,0.04032762,0.4087107],"study_design_scores_gemma":[0.0000128993,0.00005394901,0.02253021,0.00003501862,0.00002529248,0.00005666736,0.0004145007,0.9710222,0.0005805556,0.002795015,0.00245176,0.00002185941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7991979,0.001603818,0.1689381,0.003034712,0.0005792293,0.000428727,0.01453505,0.001265249,0.01041716],"genre_scores_gemma":[0.950202,0.0004399383,0.03540926,0.0001506187,0.0002463374,0.00011719,0.01017462,0.00004782538,0.003212241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02829658,"threshold_uncertainty_score":0.05626374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09698141526409826,"score_gpt":0.375991622430788,"score_spread":0.2790102071666897,"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."}}