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[null,"1.","Record Nr.",null,"UNINA9910795354403321"]
[null,null,"Titolo",null,"Using data science to understand the coronavirus pandemic / / guest editors Xin Tian, Wu He and Yunfei Xing"]
[null,null,"Pubbl/distr/stampa",null,"[Place of publication not identified] : , : Emerald Publishing Limited, , 2021"]
[null,null,"ISBN",null,"1-80262-836-3"]
[null,null,"Descrizione fisica",null,"1 online resource (81 pages)"]
[null,null,"Collana",null,"Information Discovery and Delivery, , 2398-6247 ; ; Volume 49, Number 3"]
[null,null,"Disciplina",null,"614.592414"]
[null,null,"Soggetti",null,"COVID-19 Pandemic, 2020- - Geographic information systems"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Cover -- Guest editorial -- Twitter users' coping behaviors during the COVID-19 lockdown: an analysis of tweets using mixed methods -- A comparative study of modified SIR and logistic predictors using local level database of COVID-19 in India -- An agent-based model for simulating COVID-19 transmissions on university campus and its implications on mitigation interventions: a case study -- An empirical investigation of precursors influencing social media health information behaviors and personal healthcare habits during coronavirus (COVID-19) pandemic -- An analysis of attitude of general public toward COVID-19 crises - sentimental analysis and a topic modeling study -- COVID-19 and India: what next? -- Forecasting mental health and emotions based on social media expressions during the COVID-19 pandemic."]