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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19447, 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

Journals

  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. Journal of Medical Internet Research 2021;23(6):e26655 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;27(2):179 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
  48. Jong W, Liang O, Yang C. The Exchange of Informational Support in Online Health Communities at the Onset of the COVID-19 Pandemic: Content Analysis. JMIRx Med 2021;2(3):e27485 View
  49. Herbstreit F, Overbeck M, Berger M, Skarabis A, Brenner T, Schmidt K. Characteristics of Critically Ill Patients with COVID-19 Compared to Patients with Influenza—A Single Center Experience. Journal of Clinical Medicine 2021;10(10):2056 View
  50. Jiang Y, Huang X, Li Z. Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City. ISPRS International Journal of Geo-Information 2021;10(5):344 View
  51. Kumar V, Singh D, Kaur M, Damaševičius R. Overview of current state of research on the application of artificial intelligence techniques for COVID-19. PeerJ Computer Science 2021;7:e564 View
  52. Altan A. Emotional effect of the Covid-19 pandemic on oral surgery procedures: a social media analysis. Journal of Dental Anesthesia and Pain Medicine 2021;21(3):237 View
  53. Pollack C, Gilbert-Diamond D, Alford-Teaster J, Onega T. A Longitudinal Evaluation of the Language and Sentiment About Telemedicine and COVID-19 on Twitter: Infodemiology Study (Preprint). Journal of Medical Internet Research 2021 View
  54. Schweinberger M, Haugh M, Hames S. Analysing discourse around COVID-19 in the Australian Twittersphere: A real-time corpus-based analysis. Big Data & Society 2021;8(1):205395172110214 View
  55. Ilyas H, Anwar A, Yaqub U, Alzamil Z, Appelbaum D. Analysis and visualization of COVID-19 discourse on Twitter using data science: a case study of the USA, the UK and India. Global Knowledge, Memory and Communication 2021;ahead-of-print(ahead-of-print) View
  56. Velásquez N, Leahy R, Restrepo N, Lupu Y, Sear R, Gabriel N, Jha O, Goldberg B, Johnson N. Online hate network spreads malicious COVID-19 content outside the control of individual social media platforms. Scientific Reports 2021;11(1) View
  57. Sanders J, Tosi A, Obradovic S, Miligi I, Delaney L. Lessons From the UK's Lockdown: Discourse on Behavioural Science in Times of COVID-19. Frontiers in Psychology 2021;12 View
  58. Nanath K, Joy G. Leveraging Twitter data to analyze the virality of Covid-19 tweets: a text mining approach. Behaviour & Information Technology 2021:1 View
  59. Cohrdes C, Yenikent S, Wu J, Ghanem B, Franco-Salvador M, Vogelgesang F. Indications of Depressive Symptoms During the COVID-19 Pandemic in Germany: Comparison of National Survey and Twitter Data. JMIR Mental Health 2021;8(6):e27140 View
  60. Miller M, Romine W, Oroszi T. Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events. JMIR Public Health and Surveillance 2021;7(6):e27976 View
  61. Hanschmidt F, Kersting A. Emotions in Covid-19 Twitter discourse following the introduction of social contact restrictions in Central Europe. Journal of Public Health 2021 View
  62. Kwan J, Henry M, Christophers B, Tamirisa K, Thamman R, Sadler D, Aggarwal N, Cheng R, Parwani P, Dent S, Ismail-Khan R, Fradley M, Brown S. The Role and Impact of Social Media in Cardio-oncology During the COVID-19 Pandemic. Current Oncology Reports 2021;23(8) View
  63. Li Y, Luan S, Li Y, Hertwig R. Changing emotions in the COVID-19 pandemic: A four-wave longitudinal study in the United States and China. Social Science & Medicine 2021;285:114222 View
  64. Marzouki A, Chouikh A, Mellouli S, Haddad R. From Sustainable Development Goals to Sustainable Cities: A Social Media Analysis for Policy-Making Decision. Sustainability 2021;13(15):8136 View
  65. Ahmad W, Wang B, Xu H, Xu M, Zeng Z. Topics, Sentiments, and Emotions Triggered by COVID-19-Related Tweets from IRAN and Turkey Official News Agencies. SN Computer Science 2021;2(5) View
  66. Hammes L, Rossi A, Pedrotti L, Pitrez P, Mutlaq M, Rosa R. Is the press properly presenting the epidemiological data on COVID-19? An analysis of newspapers from 25 countries. Journal of Public Health Policy 2021 View
  67. Pian W, Chi J, Ma F. The causes, impacts and countermeasures of COVID-19 “Infodemic”: A systematic review using narrative synthesis. Information Processing & Management 2021;58(6):102713 View
  68. Tan H, Peng S, Zhu C, You Z, Miao M, Kuai S. Long-term Effects of the COVID-19 Pandemic on Public Sentiments in Mainland China: Sentiment Analysis of Social Media Posts. Journal of Medical Internet Research 2021;23(8):e29150 View
  69. Pan Y, Zhang L, Yan Z, Lwin M, Skibniewski M. Discovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia. Sustainable Cities and Society 2021:103254 View

Books/Policy Documents

  1. Koinig I. Risk Management [Working Title]. View
  2. Wright K. Communicating Science in Times of Crisis. View
  3. Alsoubai A, Song J, Razi A, Dacre P, Wisniewski P. Social Computing and Social Media: Applications in Marketing, Learning, and Health. View
  4. Yan Y, Chin W, Leong C, Wang Y, Feng C. Mapping COVID-19 in Space and Time. View