A5036011418- Misinformation and Its Impacts
- Data-Driven Disease Surveillance
- Mental Health via Writing
- Vaccine Coverage and Hesitancy
- COVID-19 epidemiological studies
- COVID-19 and Mental Health
- Air Quality and Health Impacts
- Maritime Navigation and Safety
- Central Asia Education and Culture
- COVID-19 diagnosis using AI
- Law, logistics, and international trade
- China's Ethnic Minorities and Relations
Foundation for Child Development
2020-2021
Yale University
2021
Shanghai Maritime University
2014
Institute of Information Engineering
2014
Background Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts mental health and general well-being of individuals populations over time. Objective This study aimed to obtain information symptoms medical conditions self-reported by non-Twitter users during COVID-19 pandemic, determine discussion these changed time, identify correlations between frequency top 5 commonly mentioned post daily statistics (new cases, new deaths,...
Background COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement perceptions of preventive measures using social media data could provide important information for understanding progress current interventions planning future programs. Objective The aim this study is measure public’s behaviors regarding its effects on daily life during 5 months pandemic. Methods Natural language processing (NLP) algorithms were used identify COVID-19–related...
<sec> <title>BACKGROUND</title> Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts mental health and general well-being of individuals populations over time. </sec> <title>OBJECTIVE</title> This study aimed to obtain information symptoms medical conditions self-reported by non-Twitter users during COVID-19 pandemic, determine discussion these changed time, identify correlations between frequency top 5 commonly mentioned post...
<sec> <title>BACKGROUND</title> COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement perceptions of preventive measures using social media data could provide important information for understanding progress current interventions planning future programs. </sec> <title>OBJECTIVE</title> The aim this study is measure public’s behaviors regarding its effects on daily life during 5 months pandemic. <title>METHODS</title> Natural language...
Abstract Background The coronavirus disease 2019 (COVID-19) has continued to spread in the US and globally. Closely monitoring public engagement perception of COVID-19 preventive measures using social media data could provide important information for understanding progress current interventions planning future programs. Objective To measure public’s behaviors perceptions regarding its daily life effects during recent 5 months pandemic. Methods Natural language processing (NLP) algorithms...