Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19509, first published .
Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study

Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study

Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study

Frontiers in Cardiovascular Medicine

Citations:
Innovation in Precision Cardio-Oncology During the Coronavirus Pandemic and Into a Post-pandemic World View

Population Health Management

Citations:
Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals View

PLOS ONE

Citations:
Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter View

Information

Citations:
Bots as Active News Promoters: A Digital Analysis of COVID-19 Tweets View

Online Social Networks and Media

Citations:
Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis View

JMIR Medical Informatics

Citations:
Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review View

Annals of Operations Research

Citations:
Social media effectiveness as a humanitarian response to mitigate influenza epidemic and COVID-19 pandemic View

Chaos, Solitons & Fractals

Citations:
Applications of artificial intelligence in battling against covid-19: A literature review View

Journal of Medical Internet Research

Citations:
Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set View
Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach View
Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media View
Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis View

Trends in Parasitology

Citations:
iParasitology: Mining the Internet to Test Parasitological Hypotheses View

International Journal of Environmental Research and Public Health

Citations:
COVID-19: Detecting Government Pandemic Measures and Public Concerns from Twitter Arabic Data Using Distributed Machine Learning View

International Journal of Scientific Research in Science, Engineering and Technology

Citations:
Application of Machine Learning for SARS-CoV-2 Outbreak View

Acta Informatica Pragensia

Citations:
The Role of Twitter During the COVID-19 Crisis: A Systematic Literature Review View

JMIR Formative Research

Citations:
Starter Kit for Geotagging and Geovisualization in Health Care: Resource Paper View

Applied Soft Computing

Citations:
Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA View