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

Journals

  1. Brown S, Rhee J, Guha A, Rao V. Innovation in Precision Cardio-Oncology During the Coronavirus Pandemic and Into a Post-pandemic World. Frontiers in Cardiovascular Medicine 2020;7 View
  2. Picone M, Inoue S, DeFelice C, Naujokas M, Sinrod J, Cruz V, Stapleton J, Sinrod E, Diebel S, Wassman E. Social Listening as a Rapid Approach to Collecting and Analyzing COVID-19 Symptoms and Disease Natural Histories Reported by Large Numbers of Individuals. Population Health Management 2020;23(5):350 View
  3. Xue J, Chen J, Chen C, Zheng C, Li S, Zhu T, Zhao J. Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter. PLOS ONE 2020;15(9):e0239441 View
  4. Al-Rawi A, Shukla V. Bots as Active News Promoters: A Digital Analysis of COVID-19 Tweets. Information 2020;11(10):461 View
  5. Haupt M, Jinich-Diamant A, Li J, Nali M, Mackey T. Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis. Online Social Networks and Media 2021;21:100114 View
  6. Syeda H, Syed M, Sexton K, Syed S, Begum S, Syed F, Prior F, Yu Jr F. Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review. JMIR Medical Informatics 2021;9(1):e23811 View
  7. Kumar S, Xu C, Ghildayal N, Chandra C, Yang M. Social media effectiveness as a humanitarian response to mitigate influenza epidemic and COVID-19 pandemic. Annals of Operations Research 2021 View
  8. Tayarani N. M. Applications of artificial intelligence in battling against covid-19: A literature review. Chaos, Solitons & Fractals 2021;142:110338 View
  9. Klein A, Magge A, O'Connor K, Flores Amaro J, Weissenbacher D, Gonzalez Hernandez G. Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set. Journal of Medical Internet Research 2021;23(1):e25314 View
  10. Poulin R, Bennett J, Filion A, Bhattarai U, Chai X, de Angeli Dutra D, Donlon E, Doherty J, Jorge F, Milotic M, Park E, Sabadel A, Thomas L. iParasitology: Mining the Internet to Test Parasitological Hypotheses. Trends in Parasitology 2021;37(4):267 View
  11. Xue J, Chen J, Hu R, Chen C, Zheng C, Su Y, Zhu T. Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach. Journal of Medical Internet Research 2020;22(11):e20550 View
  12. Alomari E, Katib I, Albeshri A, Mehmood R. COVID-19: Detecting Government Pandemic Measures and Public Concerns from Twitter Arabic Data Using Distributed Machine Learning. International Journal of Environmental Research and Public Health 2021;18(1):282 View
  13. Saha K, Torous J, Caine E, De Choudhury M. Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media. Journal of Medical Internet Research 2020;22(11):e22600 View
  14. Alanazi E, Alashaikh A, Alqurashi S, Alanazi A. Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis. Journal of Medical Internet Research 2020;22(11):e21329 View
  15. Ayumi V. Application of Machine Learning for SARS-CoV-2 Outbreak. International Journal of Scientific Research in Science, Engineering and Technology 2021:241 View
  16. Dalili Shoaei M, Dastani M. The Role of Twitter During the COVID-19 Crisis: A Systematic Literature Review. Acta Informatica Pragensia 2020;9(2):154 View
  17. Do Q, Marc D, Plotkin M, Pickering B, Herasevich V. Starter Kit for Geotagging and Geovisualization in Health Care: Resource Paper. JMIR Formative Research 2020;4(12):e23379 View
  18. Garcia K, Berton L. Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA. Applied Soft Computing 2021;101:107057 View
  19. Celuppi I, Lima G, Rossi E, Wazlawick R, Dalmarco E. Uma análise sobre o desenvolvimento de tecnologias digitais em saúde para o enfrentamento da COVID-19 no Brasil e no mundo. Cadernos de Saúde Pública 2021;37(3) View
  20. Peterson K, Lewis J, Patterson O, Chapman A, Denhalter D, Lye P, Stevens V, Gamage S, Roselle G, Wallace K, Jones M. Automated Travel History Extraction From Clinical Notes for Informing the Detection of Emergent Infectious Disease Events: Algorithm Development and Validation. JMIR Public Health and Surveillance 2021;7(3):e26719 View
  21. Fiok K, Karwowski W, Gutierrez E, Saeidi M, Aljuaid A, Davahli M, Taiar R, Marek T, Sawyer B. A Study of the Effects of the COVID-19 Pandemic on the Experience of Back Pain Reported on Twitter® in the United States: A Natural Language Processing Approach. International Journal of Environmental Research and Public Health 2021;18(9):4543 View
  22. Sooknanan J, Mays N. Harnessing Social Media in the Modelling of Pandemics—Challenges and Opportunities. Bulletin of Mathematical Biology 2021;83(5) View
  23. Dixon B, Mukherjee S, Wiensch A, Gray M, Ferres J, Grannis S. Capturing COVID-like Symptoms At-Scale using Banner Ads: A Novel Survey Methodology Pilot using an Online News Platform (Preprint). Journal of Medical Internet Research 2020 View
  24. Cuomo R, Purushothaman V, Li J, Cai M, Mackey T. A longitudinal and geospatial analysis of COVID-19 tweets during the early outbreak period in the United States. BMC Public Health 2021;21(1) View
  25. Zhao J, Grabowska M, Kerchberger V, Smith J, Eken H, Feng Q, Peterson J, Trent Rosenbloom S, Johnson K, Wei W. ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes. Journal of Biomedical Informatics 2021;117:103748 View
  26. Gabarron E, Rivera-Romero O, Miron-Shatz T, Grainger R, Denecke K. Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review. Yearbook of Medical Informatics 2021 View
  27. Goodswen S, Barratt J, Kennedy P, Kaufer A, Calarco L, Ellis J. Machine learning and applications in microbiology. FEMS Microbiology Reviews 2021 View
  28. Shahid O, Nasajpour M, Pouriyeh S, Parizi R, Han M, Valero M, Li F, Aledhari M, Sheng Q. Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance. Journal of Biomedical Informatics 2021;117:103751 View
  29. Massey D, Huang C, Lu Y, Cohen A, Oren Y, Moed T, Matzner P, Mahajan S, Caraballo C, Kumar N, Xue Y, Ding Q, Dreyer R, Roy B, Krumholz H. Engagement with COVID-19 Public Health Measures in the United States: A Cross-Sectional Social Media Analysis from June to November 2020 (Preprint). Journal of Medical Internet Research 2020 View
  30. Schück S, Foulquié P, Mebarki A, Faviez C, Khadhar M, Texier N, Katsahian S, Burgun A, Chen X. Concerns Discussed on Chinese and French Social Media During the COVID-19 Lockdown: Comparative Infodemiology Study Based on Topic Modeling. JMIR Formative Research 2021;5(4):e23593 View
  31. Yousefinaghani S, Dara R, Mubareka S, Sharif S. Prediction of COVID-19 Waves Using Social Media and Google Search: A Case Study of the US and Canada. Frontiers in Public Health 2021;9 View