POL socmedia - outbreak identification
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{{tp|p=32283286|t=2020. Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.|pdf=|usr=008}} | {{tp|p=32283286|t=2020. Google searches for the keywords of "wash hands" predict the speed of national spread of COVID-19 outbreak among 21 countries.|pdf=|usr=008}} | ||
{{tp|p=32360605|t=2020. The COVID-19 outbreak and Google searches: Is it really the time to worry about global mental health?|pdf=|usr=008}} | {{tp|p=32360605|t=2020. The COVID-19 outbreak and Google searches: Is it really the time to worry about global mental health?|pdf=|usr=008}} | ||
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{{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}} | ||
| + | {{tp|p=32790641|t=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.|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=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}} | ||
| + | {{tp|p=32897820|t=2020. Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals.|pdf=|usr=020}} | ||
| + | {{tp|p=33078073|t=2020. How can social media analytics assist authorities in pandemic-related policy decisions? Insights from Australian states and territories.|pdf=|usr=020}} | ||
| + | {{tp|p=33083564|t=2020. Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements.|pdf=|usr=020}} | ||
| + | {{tp|p=33105920|t=2020. Geolocated Twitter-based population mobility in Victoria, Australia, during the staged COVID-19 restrictions.|pdf=|usr=020}} | ||
| + | {{tp|p=33110594|t=2020. Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.|pdf=|usr=020}} | ||
| + | {{tp|p=33134612|t=2020. Internet search data could Be used as novel indicator for assessing COVID-19 epidemic.|pdf=|usr=020}} | ||
| + | {{tp|p=33153071|t=2020. Containing COVID-19 by Matching Messages on Social Distancing to Emergent Mindsets-The Case of North America.|pdf=|usr=020}} | ||
| + | {{tp|p=33170889|t=2020. Twitter reveals human mobility dynamics during the COVID-19 pandemic.|pdf=|usr=020}} | ||
| + | {{tp|p=33173810|t=2020. Uncovering temporal differences in COVID-19 tweets.|pdf=|usr=020}} | ||
| + | {{tp|p=33173827|t=2020. A preliminary investigation of COVID-19 transmission in the United States by incorporating social media sentiments.|pdf=|usr=020}} | ||
| + | {{tp|p=33173828|t=2020. Social media and COVID-19: Can social distancing be quantified without measuring human movements?|pdf=|usr=020}} | ||
| + | {{tp|p=33190468|t=2020. Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter.|pdf=|usr=020}} | ||
| + | {{tp|p=33284782|t=2020. Addressing Public Health Emergencies via Facebook Surveys: Advantages, Challenges, and Practical Considerations.|pdf=|usr=022}} | ||
| + | {{tp|p=33287607|t=2020. The association between COVID-19 cases and deaths and web-based public inquiries.|pdf=|usr=022}} | ||
| + | {{tp|p=33290760|t=2020. Exploring the link between risk perception in Internet media and COVID-19 prevalence in Europe.|pdf=|usr=022}} | ||
| + | {{tp|p=C7283848|t=?. Social Network Analysis for Coronavirus (COVID?19) in the United States.|pdf=|usr=015}} | ||
| + | {{tp|p=32316647|t=2020. Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China |pdf=|usr=}} | ||
| + | |||
| + | {{tp|p=C7333788|t=?. DOT: a crowdsourcing Mobile application for disease outbreak detection and surveillance in Mauritius.|pdf=|usr=015}} | ||
Aktuelle Version vom 5. Januar 2021, 20:07 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.
32897820 2020. Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals.
33078073 2020. How can social media analytics assist authorities in pandemic-related policy decisions? Insights from Australian states and territories.
33083564 2020. Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements.
33105920 2020. Geolocated Twitter-based population mobility in Victoria, Australia, during the staged COVID-19 restrictions.
33110594 2020. Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.
33134612 2020. Internet search data could Be used as novel indicator for assessing COVID-19 epidemic.
33153071 2020. Containing COVID-19 by Matching Messages on Social Distancing to Emergent Mindsets-The Case of North America.
33170889 2020. Twitter reveals human mobility dynamics during the COVID-19 pandemic.
33173810 2020. Uncovering temporal differences in COVID-19 tweets.
33173827 2020. A preliminary investigation of COVID-19 transmission in the United States by incorporating social media sentiments.
33173828 2020. Social media and COVID-19: Can social distancing be quantified without measuring human movements?
33190468 2020. Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter.
33284782 2020. Addressing Public Health Emergencies via Facebook Surveys: Advantages, Challenges, and Practical Considerations.
33287607 2020. The association between COVID-19 cases and deaths and web-based public inquiries.
33290760 2020. Exploring the link between risk perception in Internet media and COVID-19 prevalence in Europe.
C7283848 ?. Social Network Analysis for Coronavirus (COVID?19) in the United States.
32316647 2020. Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China
C7333788 ?. DOT: a crowdsourcing Mobile application for disease outbreak detection and surveillance in Mauritius.
