POL socmedia - outbreak identification
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{{tp|p=32834831|t=2020. An IoT-based framework for early identification and monitoring of COVID-19 cases.|pdf=|usr=018}} | {{tp|p=32834831|t=2020. An IoT-based framework for early identification and monitoring of COVID-19 cases.|pdf=|usr=018}} | ||
{{tp|p=32897373|t=2020. Association of Mobile Phone Location Data Indications of Travel and Stay-at-Home Mandates With COVID-19 Infection Rates in the US.|pdf=|usr=019}} | {{tp|p=32897373|t=2020. Association of Mobile Phone Location Data Indications of Travel and Stay-at-Home Mandates With COVID-19 Infection Rates in the US.|pdf=|usr=019}} | ||
| + | {{tp|p=32905027|t=2020. Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis.|pdf=|usr=019}} | ||
| + | {{tp|p=32924141|t=2020. Australia can use population level mobility data to fight COVID-19.|pdf=|usr=019}} | ||
| + | {{tp|p=32931439|t=2020. Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study.|pdf=|usr=019}} | ||
| + | {{tp|p=32937679|t=2020. Mining twitter to explore the emergence of COVID-19 symptoms.|pdf=|usr=019}} | ||
| + | {{tp|p=32946835|t=2020. Associations between phone mobility data and COVID-19 cases.|pdf=|usr=019}} | ||
Version vom 22. Dezember 2020, 21:47 Uhr
| Politics main page |
contents and metadata providers
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.
32790641 2020. Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19-Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study.
32834831 2020. An IoT-based framework for early identification and monitoring of COVID-19 cases.
32897373 2020. Association of Mobile Phone Location Data Indications of Travel and Stay-at-Home Mandates With COVID-19 Infection Rates in the US.
32905027 2020. Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis.
32924141 2020. Australia can use population level mobility data to fight COVID-19.
32931439 2020. Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study.
32937679 2020. Mining twitter to explore the emergence of COVID-19 symptoms.
32946835 2020. Associations between phone mobility data and COVID-19 cases.
