Published on in Vol 22, No 4 (2020): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19118, first published .
Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach

Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach

Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach

Journals

  1. Petrova L, Kuznetsova T, Volodin V. Post-Pandemic Scenarios of Economic Development of Developed Countries and Russia. Finance: Theory and Practice 2020;24(4):47 View
  2. Golinelli D, Boetto E, Carullo G, Nuzzolese A, Landini M, Fantini M. Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature. Journal of Medical Internet Research 2020;22(11):e22280 View
  3. Akarturk B. The Role and Challenges of Using Digital Tools for COVID-19 Contact Tracing. The European Journal of Social & Behavioural Sciences 2020;29(3):208 View
  4. Al-Hasan A, Yim D, Khuntia J. Citizens’ Adherence to COVID-19 Mitigation Recommendations by the Government: A 3-Country Comparative Evaluation Using Web-Based Cross-Sectional Survey Data. Journal of Medical Internet Research 2020;22(8):e20634 View
  5. Huang Q, Kang Y. Mathematical Modeling of COVID-19 Control and Prevention Based on Immigration Population Data in China: Model Development and Validation. JMIR Public Health and Surveillance 2020;6(2):e18638 View
  6. Badell-Grau R, Cuff J, Kelly B, Waller-Evans H, Lloyd-Evans E. Investigating the Prevalence of Reactive Online Searching in the COVID-19 Pandemic: Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e19791 View
  7. 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
  8. Waggoner P. Community Detection in Google Searches Related to “Coronavirus”. Journal of Data Science 2021:334 View
  9. Lupton D, Lewis S. Learning about COVID-19: a qualitative interview study of Australians’ use of information sources. BMC Public Health 2021;21(1) View
  10. Boon-Itt S, Skunkan Y. Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study. JMIR Public Health and Surveillance 2020;6(4):e21978 View
  11. Shah A, Yan X, Qayyum A, Naqvi R, Shah S. Mining topic and sentiment dynamics in physician rating websites during the early wave of the COVID-19 pandemic: Machine learning approach. International Journal of Medical Informatics 2021;149:104434 View
  12. Kaveh-Yazdy F, Zarifzadeh S. Track Iran's national COVID-19 response committee’s major concerns using two-stage unsupervised topic modeling. International Journal of Medical Informatics 2021;145:104309 View
  13. Li J, Wang B, Ni A, Liu Q. Text Mining Analysis on Users’ Reviews for News Aggregator Toutiao. Journal of Physics: Conference Series 2021;1771(1):012008 View
  14. Li W, Sun K, Zhu Y, Song J, Yang J, Qian L, Wang S. Analyzing the Research Evolution in Response to COVID-19. ISPRS International Journal of Geo-Information 2021;10(4):237 View
  15. 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
  16. Do B, Tran T, Phan D, Nguyen H, Nguyen T, Nguyen H, Ha T, Dao H, Trinh M, Do T, Nguyen H, Vo T, Nguyen N, Tran C, Tran K, Duong T, Pham H, Nguyen L, Nguyen K, Chang P, Duong T. Health Literacy, eHealth Literacy, Adherence to Infection Prevention and Control Procedures, Lifestyle Changes, and Suspected COVID-19 Symptoms Among Health Care Workers During Lockdown: Online Survey. Journal of Medical Internet Research 2020;22(11):e22894 View
  17. Zhou P, He Y, Lyu C, Yang X. Characterizing News Report of the Substandard Vaccine Case of Changchun Changsheng in China: A Text Mining Approach. Vaccines 2020;8(4):691 View
  18. Browning M, Larson L, Sharaievska I, Rigolon A, McAnirlin O, Mullenbach L, Cloutier S, Vu T, Thomsen J, Reigner N, Metcalf E, D'Antonio A, Helbich M, Bratman G, Alvarez H, Lin C. Psychological impacts from COVID-19 among university students: Risk factors across seven states in the United States. PLOS ONE 2021;16(1):e0245327 View
  19. Jang H, Rempel E, Roth D, Carenini G, Janjua N. Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis. Journal of Medical Internet Research 2021;23(2):e25431 View
  20. Älgå A, Eriksson O, Nordberg M. Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study. Journal of Medical Internet Research 2020;22(11):e21559 View
  21. Chan A, Wu C, Cheung A, Succi M. Characterization of an Open-Access Medical News Platform’s Readership During the COVID-19 Pandemic: Retrospective Observational Study. Journal of Medical Internet Research 2021;23(5):e26666 View
  22. 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
  23. Caulfield T, Bubela T, Kimmelman J, Ravitsky V, Blais J. Let’s do better: public representations of COVID-19 science. FACETS 2021;6(1):403 View
  24. Xue L, Jing S, Sun W, Liu M, Peng Z, Zhu H. Evaluating the impact of the travel ban within mainland China on the epidemic of the COVID-19. International Journal of Infectious Diseases 2021;107:278 View
  25. Grabowski D, Overgaard M, Meldgaard J, Johansen L, Willaing I. Disrupted Self-Management and Adaption to New Diabetes Routines: A Qualitative Study of How People with Diabetes Managed Their Illness during the COVID-19 Lockdown. Diabetology 2021;2(1):1 View
  26. Obiała J, Obiała K, Mańczak M, Owoc J, Olszewski R. COVID-19 misinformation: Accuracy of articles about coronavirus prevention mostly shared on social media. Health Policy and Technology 2021;10(1):182 View
  27. de Melo T, Figueiredo C. Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach. JMIR Public Health and Surveillance 2021;7(2):e24585 View
  28. Ghasiya P, Okamura K. Investigating COVID-19 News Across Four Nations: A Topic Modeling and Sentiment Analysis Approach. IEEE Access 2021;9:36645 View
  29. Wen F, Ye H, Wang Y, Xu Y, Zuo B. Icing on the Cake: “Amplification Effect” of Innovative Information Form in News Reports About COVID-19. Frontiers in Psychology 2021;12 View
  30. 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
  31. Zhang P. Analysis of the Public Health Functions of the Chinese Government in the Prevention and Control of COVID-19. Risk Management and Healthcare Policy 2021;Volume 14:237 View
  32. Sauer M, Truelove S, Gerste A, Limaye R. A Failure to Communicate? How Public Messaging Has Strained the COVID-19 Response in the United States. Health Security 2021;19(1):65 View
  33. Herman A. Indonesian government’s public communication management during a pandemic. Problems and Perspectives in Management 2021;19(1):244 View
  34. 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
  35. 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
  36. Massarani L, Neves L. Communicating the “Race” for the COVID-19 Vaccine: An Exploratory Study in Newspapers in the United States, the United Kingdom, and Brazil. Frontiers in Communication 2021;6 View
  37. Marcoux T, Galeano K, Galeano R, DiCicco K, Al Rubaye H, Mead E, Agarwal N, Galeano A. A public online resource to track COVID-19 misinfodemic. Social Network Analysis and Mining 2021;11(1) View
  38. Yaseen M, Saif A, Khan T, Yaseen M. Public Knowledge and Adherence to Hand Hygienic Guidelines for the Prevention of SARS-CoV-2 Transmission: A Cross-sectional Survey from Pakistan. Disaster Medicine and Public Health Preparedness 2021:1 View
  39. MURATDAĞI G, SARICA E, KÖSE E, UNGAN S, AYDIN M, AYDIN A, AKAR E, TÜRKMEN A, ETÇİOĞLU E, ARSLAN E, ARIKAN A, ÖKSÜZ A, BÜYÜKDERELİ ATADAĞ Y. The evaluation of the news related to coronavirus in national media before and after the first declared case inTurkey. Konuralp Tıp Dergisi 2021 View
  40. Lee K, Kim B, Nan D, Kim J. Structural Topic Model Analysis of Mask-Wearing Issue Using International News Big Data. International Journal of Environmental Research and Public Health 2021;18(12):6432 View
  41. Tri Sakti A, Mohamad E, Azlan A. Mining of Opinions on COVID-19 Large-Scale Social Restrictions in Indonesia: Public Sentiment and Emotion Analysis on Online Media. Journal of Medical Internet Research 2021;23(8):e28249 View
  42. Gamsizkan Z, Kaya A, Sungur M. The Increasing Importance of the e-Health System after the COVID-19 Outbreak with New Healthcare Expectations. Eurasian Journal of Family Medicine 2021;10(2):84 View
  43. Er Saw P. BIOI Virtual Academic Series PART 1: Multidisciplinary Integration in Academia. BIO Integration 2020;1(2):101 View
  44. Jiang M, Dodoo N. Promoting Mask-Wearing in COVID-19 Brand Communications: Effects of Gain-Loss Frames, Self- or Other-Interest Appeals, and Perceived Risks. Journal of Advertising 2021;50(3):271 View
  45. Krawczyk K, Chelkowski T, Laydon D, Mishra S, Xifara D, Gibert B, Flaxman S, Mellan T, Schwämmle V, Röttger R, Hadsund J, Bhatt S. Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource. Journal of Medical Internet Research 2021;23(6):e28253 View
  46. Jafarinejad F, Rahimi M, Mashayekhi H. Tracking and analysis of discourse dynamics and polarity during the early Corona pandemic in Iran. Journal of Biomedical Informatics 2021;121:103862 View
  47. Wang Y, Shi M, Zhang J, Feng G. What public health campaigns can learn from people’s Twitter reactions on mask-wearing and COVID-19 Vaccines: a topic modeling approach. Cogent Social Sciences 2021;7(1):1959728 View
  48. Stevens H, Oh Y, Taylor L. Desensitization to Fear-Inducing COVID-19 Health News on Twitter: Observational Study. JMIR Infodemiology 2021;1(1):e26876 View
  49. Patel J, Desai H, Okhowat A. The Role of the Canadian Media During the Initial Response to the COVID-19 Pandemic: A Topic Modelling Approach Using Canadian Broadcasting Corporation News Articles. JMIR Infodemiology 2021;1(1):e25242 View
  50. Atif M, Ahmad M, Malik I, Muhstaq I, Ahmad N, Mehjabin , Babar Z. How medicines sales staff is responding to presumptive COVID‐19 patients attending drug retail outlets: An exploratory qualitative study. The International Journal of Health Planning and Management 2021 View