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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18700, first published .
Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study

Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study

Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study

Journals

  1. Pobiruchin M, Zowalla R, Wiesner M. 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. Journal of Medical Internet Research 2020;22(8):e19629 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. Zhang D, Zhou L, Lim J. From Networking to Mitigation: The Role of Social Media and Analytics in Combating the COVID-19 Pandemic. Information Systems Management 2020;37(4):318 View
  4. Campos-Castillo C, Laestadius L. Racial and Ethnic Digital Divides in Posting COVID-19 Content on Social Media Among US Adults: Secondary Survey Analysis. Journal of Medical Internet Research 2020;22(7):e20472 View
  5. Liao Q, Yuan J, Dong M, Yang L, Fielding R, Lam W. Public Engagement and Government Responsiveness in the Communications About COVID-19 During the Early Epidemic Stage in China: Infodemiology Study on Social Media Data. Journal of Medical Internet Research 2020;22(5):e18796 View
  6. Shen C, Chen A, Luo C, Zhang J, Feng B, Liao W. Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study. Journal of Medical Internet Research 2020;22(5):e19421 View
  7. Mackey T, Purushothaman V, Li J, Shah N, Nali M, Bardier C, Liang B, Cai M, Cuomo R. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study. JMIR Public Health and Surveillance 2020;6(2):e19509 View
  8. Ahmed W, Vidal-Alaball J, Downing J, López Seguí F. COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. Journal of Medical Internet Research 2020;22(5):e19458 View
  9. Peng Z, Wang R, Liu L, Wu H. Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data. ISPRS International Journal of Geo-Information 2020;9(6):402 View
  10. Walrave M, Waeterloos C, Ponnet K. Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach. JMIR Public Health and Surveillance 2020;6(3):e20572 View
  11. Eltoukhy A, Shaban I, Chan F, Abdel-Aal M. Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations. International Journal of Environmental Research and Public Health 2020;17(19):7080 View
  12. Xu Q, Shen Z, Shah N, Cuomo R, Cai M, Brown M, Li J, Mackey T. Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis. JMIR Public Health and Surveillance 2020;6(4):e24125 View
  13. Burzyńska J, Bartosiewicz A, Rękas M. The social life of COVID-19: Early insights from social media monitoring data collected in Poland. Health Informatics Journal 2020;26(4):3056 View
  14. Galehdar N, Toulabi T, Kamran A, Heydari H. Exploring nurses’ perception about the care needs of patients with COVID-19: a qualitative study. BMC Nursing 2020;19(1) View
  15. Tayarani N. M. Applications of artificial intelligence in battling against covid-19: A literature review. Chaos, Solitons & Fractals 2021;142:110338 View
  16. Shahsavari S, Holur P, Wang T, Tangherlini T, Roychowdhury V. Conspiracy in the time of corona: automatic detection of emerging COVID-19 conspiracy theories in social media and the news. Journal of Computational Social Science 2020;3(2):279 View
  17. Chen S, Zhou L, Song Y, Xu Q, Wang P, Wang K, Ge Y, Janies D. A Novel Machine Learning Framework for Comparison of Viral COVID-19–Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis. Journal of Medical Internet Research 2021;23(1):e24889 View
  18. Gencoglu O, Gruber M. Causal Modeling of Twitter Activity during COVID-19. Computation 2020;8(4):85 View
  19. Huang W, Cao B, Yang G, Luo N, Chao N. Turn to the Internet First? Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend. Information Processing & Management 2021;58(3):102486 View
  20. Guo F, Tang B, Qin D, Zhao T, Su Y, McGrath C, Hua F, He H. The Impact of the COVID-19 Epidemic on Orthodontic Patients in China: An Analysis of Posts on Weibo. Frontiers in Medicine 2020;7 View
  21. Chang A, Schulz P, Tu S, Liu M. Communicative Blame in Online Communication of the COVID-19 Pandemic: Computational Approach of Stigmatizing Cues and Negative Sentiment Gauged With Automated Analytic Techniques. Journal of Medical Internet Research 2020;22(11):e21504 View
  22. Chandrasekaran R, Mehta V, Valkunde T, Moustakas E. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e22624 View
  23. Chang C, Monselise M, Yang C. What Are People Concerned About During the Pandemic? Detecting Evolving Topics about COVID-19 from Twitter. Journal of Healthcare Informatics Research 2021;5(1):70 View
  24. 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
  25. Tsao S, Chen H, Tisseverasinghe T, Yang Y, Li L, Butt Z. What social media told us in the time of COVID-19: a scoping review. The Lancet Digital Health 2021;3(3):e175 View
  26. Basch C, Fera J, Pierce I, Basch C. Promoting Mask Use on TikTok: Descriptive, Cross-sectional Study. JMIR Public Health and Surveillance 2021;7(2):e26392 View
  27. Mahmoud H, Taha M, Askoura A, Aleem M, Omran A, Aboelela S. Can chest CT improve sensitivity of COVID-19 diagnosis in comparison to PCR? A meta-analysis study. The Egyptian Journal of Otolaryngology 2020;36(1) View
  28. Luo C, Li Y, Chen A, Tang Y, Capraro V. What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media. PLOS ONE 2020;15(11):e0241465 View
  29. Rao Q, Zhang Z, Lv Y, Zhao Y, Bai L, Hou X. Factors Associated With Influential Health-Promoting Messages on Social Media: Content Analysis of Sina Weibo. JMIR Medical Informatics 2020;8(10):e20558 View
  30. 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
  31. Lyu J, Luli G. Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study. Journal of Medical Internet Research 2021;23(2):e25108 View
  32. Geronikolou S, Chrousos G. COVID-19–Induced Fear in Infoveillance Studies: Pilot Meta-analysis Study of Preliminary Results. JMIR Formative Research 2021;5(2):e21156 View
  33. Wang X, Chen L, Shi J, Tang H. Who Sets the Agenda? the Dynamic Agenda Setting of the Wildlife Issue on Social Media. Environmental Communication 2021:1 View
  34. Zhou Q, Zhang C. Breaking community boundary: Comparing academic and social communication preferences regarding global pandemics. Journal of Informetrics 2021;15(3):101162 View
  35. Domalewska D. An analysis of COVID-19 economic measures and attitudes: evidence from social media mining. Journal of Big Data 2021;8(1) View
  36. 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
  37. Cai Z, Zheng S, Huang Y, Au W, Qiu Z, Wu K. The Interactive Effects of Cognition on Coping Styles among Chinese during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2021;18(6):3148 View
  38. 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
  39. 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
  40. Shah A, Naqvi R, Jeong O. Detecting Topic and Sentiment Trends in Physician Rating Websites: Analysis of Online Reviews Using 3-Wave Datasets. International Journal of Environmental Research and Public Health 2021;18(9):4743 View
  41. Safdari R, Rezayi S, Saeedi S, Tanhapour M, Gholamzadeh M. Using data mining techniques to fight and control epidemics: A scoping review. Health and Technology 2021 View

Books/Policy Documents

  1. Chen L, Huang X, Zhang H, Niu B. Machine Learning for Cyber Security. View
  2. Wright K. Communicating Science in Times of Crisis. View