POL socmedia - outbreak identification
Zeile 5: | Zeile 5: | ||
{{tp|p=32490846|t=2020. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study.|pdf=|usr=007}} | {{tp|p=32490846|t=2020. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study.|pdf=|usr=007}} | ||
{{tp|p=32530937|t=2020. Studying health-related internet and mobile device use using web logs and smartphone records.|pdf=|usr=015}} | {{tp|p=32530937|t=2020. Studying health-related internet and mobile device use using web logs and smartphone records.|pdf=|usr=015}} | ||
+ | {{tp|p=32575957|t=2020. Use of Twitter social media activity as a proxy for human mobility to predict the spatiotemporal spread of COVID-19 at global scale.|pdf=|usr=010}} |
Version vom 6. Dezember 2020, 13:54 Uhr
32283286 2020. Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.
32360605 2020. The COVID-19 outbreak and Google searches: Is it really the time to worry about global mental health?
32360607 2020. Google Trends provides a tool to monitor population concerns and information needs during COVID-19 pandemic.
32401211 2020. Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study.
32490846 2020. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study.
32530937 2020. Studying health-related internet and mobile device use using web logs and smartphone records.
32575957 2020. Use of Twitter social media activity as a proxy for human mobility to predict the spatiotemporal spread of COVID-19 at global scale.