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

Preprints (earlier versions) of this paper are available at, first published .
Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends

Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends

Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends


  1. Chivers B, Garad R, Boyle J, Skouteris H, Teede H, Harrison C. Perinatal Distress During COVID-19: Thematic Analysis of an Online Parenting Forum. Journal of Medical Internet Research 2020;22(9):e22002 View
  2. Al-Rawi A, Shukla V. Bots as Active News Promoters: A Digital Analysis of COVID-19 Tweets. Information 2020;11(10):461 View
  3. 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
  4. 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
  5. 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
  6. Villapol S. Gastrointestinal symptoms associated with COVID-19: impact on the gut microbiome. Translational Research 2020;226:57 View
  7. 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
  8. Da T, Yang L. Local COVID-19 Severity and Social Media Responses: Evidence From China. IEEE Access 2020;8:204684 View
  9. SALAMEH P, HAJJ A, BADRO D, ABOU SELWAN C, AOUN R, SACRE H. Mental Health Outcomes of the COVID-19 Pandemic and a Collapsing Economy: Perspectives from a Developing Country. Psychiatry Research 2020;294:113520 View
  10. 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
  11. 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
  12. Ojo A, Guntuku S, Zheng M, Beidas R, Ranney M. How Health Care Workers Wield Influence Through Twitter Hashtags: Retrospective Cross-sectional Study of the Gun Violence and COVID-19 Public Health Crises. JMIR Public Health and Surveillance 2021;7(1):e24562 View
  13. 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
  14. Jiang P, Klemeš J, Fan Y, Fu X, Bee Y. More Is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment Is Crucial. International Journal of Environmental Research and Public Health 2021;18(2):684 View
  15. 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
  16. Lamsal R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence 2020 View
  17. Chang W. The influences of the COVID-19 pandemic on medical service behaviors. Taiwanese Journal of Obstetrics and Gynecology 2020;59(6):821 View
  18. 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
  19. DePaul A. How to shift into COVID-19 research. Nature 2020 View
  20. Chou W, Budenz A. Considering Emotion in COVID-19 Vaccine Communication: Addressing Vaccine Hesitancy and Fostering Vaccine Confidence. Health Communication 2020;35(14):1718 View
  21. Pellert M, Lasser J, Metzler H, Garcia D. Dashboard of Sentiment in Austrian Social Media During COVID-19. Frontiers in Big Data 2020;3 View
  22. Stella M. Cognitive Network Science Reconstructs How Experts, News Outlets and Social Media Perceived the COVID-19 Pandemic. Systems 2020;8(4):38 View
  23. Murlimanju B, Mishra R, Mohan R, Kosagi S, Agrawal A. Letter to the Editor Regarding: “A Surprise Sabbatical: How Mayo Clinic Neurosurgery Coped with Coronavirus Disease 2019”. World Neurosurgery 2020;144:328 View
  24. Chen N, Zhong Z, Pang J. An Exploratory Study of COVID-19 Information on Twitter in the Greater Region. Big Data and Cognitive Computing 2021;5(1):5 View
  25. Alamoodi A, Zaidan B, Zaidan A, Albahri O, Mohammed K, Malik R, Almahdi E, Chyad M, Tareq Z, Albahri A, Hameed H, Alaa M. Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. Expert Systems with Applications 2021;167:114155 View
  26. 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
  27. S.V. P, Ittamalla R. An analysis of attitude of general public toward COVID-19 crises – sentimental analysis and a topic modeling study. Information Discovery and Delivery 2021;ahead-of-print(ahead-of-print) View
  28. 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
  29. 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
  30. Fingerman K, Ng Y, Zhang S, Britt K, Colera G, Birditt K, Charles S, Carr D. Living Alone During COVID-19: Social Contact and Emotional Well-being Among Older Adults. The Journals of Gerontology: Series B 2021;76(3):e116 View
  31. Zhang C, Xu S, Li Z, Hu S. Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study. Journal of Medical Internet Research 2021;23(3):e26482 View
  32. 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
  33. Al-Laith A, Alenezi M. Monitoring People’s Emotions and Symptoms from Arabic Tweets during the COVID-19 Pandemic. Information 2021;12(2):86 View
  34. Ryu S, Park I, Kim M, Lee Y, Lee J, Kim H, Jhon M, Kim J, Lee J, Kim J, Kim S, Nishi A. Network study of responses to unusualness and psychological stress during the COVID-19 outbreak in Korea. PLOS ONE 2021;16(2):e0246894 View
  35. 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
  36. Priadana A, Tahalea S. Hashtag activism and message frames: social network analysis of Instagram during the COVID-19 pandemic outbreak in Indonesia. Journal of Physics: Conference Series 2021;1836(1):012031 View
  37. Yu S, Eisenman D, Han Z. Temporal Dynamics of Public Emotions During the COVID-19 Pandemic at the Epicenter of the Outbreak: Sentiment Analysis of Weibo Posts From Wuhan. Journal of Medical Internet Research 2021;23(3):e27078 View
  38. 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
  39. Chum A, Nielsen A, Bellows Z, Farrell E, Durette P, Banda J, Cupchik G. Changes in public response associated with various COVID-19 restrictions in Ontario, Canada: an observational study using social media time series data (Preprint). Journal of Medical Internet Research 2021 View
  40. 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
  41. Wicke P, Bolognesi M. Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time. Frontiers in Communication 2021;6 View
  42. 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
  43. Feng S, Kirkley A. Integrating online and offline data for crisis management: Online geolocalized emotion, policy response, and local mobility during the COVID crisis. Scientific Reports 2021;11(1) View
  44. Ng L, Carley K. “The coronavirus is a bioweapon”: classifying coronavirus stories on fact-checking sites. Computational and Mathematical Organization Theory 2021 View
  45. 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
  46. Ismael F, Bizario J, Battagin T, Zaramella B, Leal F, Torales J, Ventriglio A, Marziali M, Martins S, Castaldelli-Maia J. Post-infection depressive, anxiety and post-traumatic stress symptoms: A prospective cohort study in patients with mild COVID-19. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2021;111:110341 View
  47. Mwendwa P, Githui S, Marete E, Kroll T. COVID-19 and vaccines in Africa: a descriptive and thematic analysis of Twitter content. HRB Open Research 2021;4:43 View

Books/Policy Documents

  1. Koinig I. Risk Management [Working Title]. View
  2. Wright K. Communicating Science in Times of Crisis. View