Using data science to understand the coronavirus pandemic / / guest editors Xin Tian, Wu He and Yunfei Xing
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| Titolo: |
Using data science to understand the coronavirus pandemic / / guest editors Xin Tian, Wu He and Yunfei Xing
|
| Pubblicazione: | [Place of publication not identified] : , : Emerald Publishing Limited, , 2021 |
| Descrizione fisica: | 1 online resource (81 pages) |
| Disciplina: | 614.592414 |
| Soggetto topico: | COVID-19 Pandemic, 2020- - Geographic information systems |
| Persona (resp. second.): | TianXin |
| HeWu | |
| XingYunfei | |
| Nota di contenuto: | 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. |
| Titolo autorizzato: | Using data science to understand the coronavirus pandemic |
| ISBN: | 1-80262-836-3 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910795354403321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Information Discovery and Delivery