{"id":"W3094221957","doi":"10.2196/21978","title":"Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study","year":2020,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":506,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Topic model; Latent Dirichlet allocation; Sentiment analysis; Pandemic; Coronavirus disease 2019 (COVID-19); Categorization; Preparedness; Social media; Data science; Computer science; Psychology; Natural language processing; Political science; Disease; Medicine; Artificial intelligence; World Wide Web; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1953344707090537,"score_gpt":0.3991104072319475,"score_spread":0.2037759365228938,"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."}}