This paper is in the following e-collection/theme issue:

Natural Language Processing (507) JMIR Theme Issue: COVID-19 Special Issue (2168) Outbreak and Pandemic Preparedness and Management (1492) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1361) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1323) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (863) Infodemiology and Infoveillance (1047) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (346)

Published on in Vol 9 , No 4 (2021) :April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22734, first published .
Health, Psychosocial, and Social Issues Emanating From the COVID-19 Pandemic Based on Social Media Comments: Text Mining and Thematic Analysis Approach

Health, Psychosocial, and Social Issues Emanating From the COVID-19 Pandemic Based on Social Media Comments: Text Mining and Thematic Analysis Approach

Health, Psychosocial, and Social Issues Emanating From the COVID-19 Pandemic Based on Social Media Comments: Text Mining and Thematic Analysis Approach

Authors of this article:

Oladapo Oyebode 1 Author Orcid Image ;   Chinenye Ndulue 1 Author Orcid Image ;   Ashfaq Adib 1 Author Orcid Image ;   Dinesh Mulchandani 1 Author Orcid Image ;   Banuchitra Suruliraj 1 Author Orcid Image ;   Fidelia Anulika Orji 2 Author Orcid Image ;   Christine T Chambers 3, 4 Author Orcid Image ;   Sandra Meier 5 Author Orcid Image ;   Rita Orji 1 Author Orcid Image
Article Authors Cited by (24) Tweetations (5) Metrics

Journals

  1. CARDINALE M. Preparing athletes and staff for the first "pandemic" Olympic Games. The Journal of Sports Medicine and Physical Fitness 2021;61(8) View
  2. Marcec R, Likic R. Using Twitter for sentiment analysis towards AstraZeneca/Oxford, Pfizer/BioNTech and Moderna COVID-19 vaccines. Postgraduate Medical Journal 2022;98(1161):544 View
  3. Teague S, Shatte A, Weller E, Fuller-Tyszkiewicz M, Hutchinson D. Methods and Applications of Social Media Monitoring of Mental Health During Disasters: Scoping Review. JMIR Mental Health 2022;9(2):e33058 View
  4. Al-Garadi M, Yang Y, Sarker A. The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges. Healthcare 2022;10(11):2270 View
  5. Oyebode O, Ndulue C, Mulchandani D, Suruliraj B, Adib A, Orji F, Milios E, Matwin S, Orji R. COVID-19 Pandemic: Identifying Key Issues Using Social Media and Natural Language Processing. Journal of Healthcare Informatics Research 2022;6(2):174 View
  6. Qorib M, Oladunni T, Denis M, Ososanya E, Cotae P. Covid-19 vaccine hesitancy: Text mining, sentiment analysis and machine learning on COVID-19 vaccination Twitter dataset. Expert Systems with Applications 2023;212:118715 View
  7. Oyebode O, Orji R. Identifying adverse drug reactions from patient reviews on social media using natural language processing. Health Informatics Journal 2023;29(1):146045822211367 View
  8. Bakuri A, Antwi-Berko D. “What Other Information Is There?”: Identifying Information Gaps, Perceptions and Misconceptions on COVID-19 Among Minority Ethnic Groups in the Netherlands. Frontiers in Health Services 2022;2 View
  9. Chen Z, Kwak D. It’s Okay to be Not Okay: An Analysis of Twitter Responses to Naomi Osaka’s Withdrawal due to Mental Health Concerns. Communication & Sport 2023;11(3):439 View
  10. Huangfu L, Mo Y, Zhang P, Zeng D, He S. COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling. Journal of Medical Internet Research 2022;24(2):e31726 View
  11. Alabrah A, Alawadh H, Okon O, Meraj T, Rauf H. Gulf Countries’ Citizens’ Acceptance of COVID-19 Vaccines—A Machine Learning Approach. Mathematics 2022;10(3):467 View
  12. Bhuptani P, Hunter J, Goodwin C, Millman C, Orchowski L. Characterizing Intimate Partner Violence in the United States During the COVID-19 Pandemic: A Systematic Review. Trauma, Violence, & Abuse 2022:152483802211261 View
  13. Gómez-Salgado J, Palomino-Baldeón J, Ortega-Moreno M, Fagundo-Rivera J, Allande-Cussó R, Ruiz-Frutos C. COVID-19 information received by the Peruvian population, during the first phase of the pandemic, and its association with developing psychological distress. Medicine 2022;101(5):e28625 View
  14. Weger R, Lossio-Ventura J, Rose-McCandlish M, Shaw J, Sinclair S, Pereira F, Chung J, Atlas L. Trends in Language Use During the COVID-19 Pandemic and Relationship Between Language Use and Mental Health: Text Analysis Based on Free Responses From a Longitudinal Study. JMIR Mental Health 2023;10:e40899 View
  15. Oduntan A, Oyebode O, Beltran A, Fowles J, Steeves D, Orji R. “I Let Depression and Anxiety Drown Me…”: Identifying Factors Associated With Resilience Based on Journaling Using Machine Learning and Thematic Analysis. IEEE Journal of Biomedical and Health Informatics 2022;26(7):3397 View
  16. Wang Y, Croucher S, Pearson E. National Leaders’ Usage of Twitter in Response to COVID-19: A Sentiment Analysis. Frontiers in Communication 2021;6 View
  17. Castilla-Puentes R, Pesa J, Brethenoux C, Furey P, Gil Valletta L, Falcone T. Applying the Health Belief Model to Characterize Racial/Ethnic Differences in Digital Conversations Related to Depression Pre- and Mid-COVID-19: Descriptive Analysis. JMIR Formative Research 2022;6(6):e33637 View
  18. Gélinas-Gascon F, Khoury R. Modeling and Moderation of COVID-19 Social Network Chat. Information 2023;14(2):124 View
  19. Nia Z, Ahmadi A, Bragazzi N, Woldegerima W, Mellado B, Wu J, Orbinski J, Asgary A, Kong J, Valls Martínez M. A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments. PLOS ONE 2022;17(8):e0272208 View
  20. Nia Z, Ahmadi A, Bragazzi N, Woldegerima W, Mellado B, Wu J, Orbinski J, Asgary A, Kong J. A Cross-Country Analysis of Macroeconomic Responses to COVID-19 Pandemic Using Twitter Sentiments. SSRN Electronic Journal 2022 View

Books/Policy Documents

  1. . Applied Big Data Analytics and Its Role in COVID-19 Research. View
  2. Wetter T. Personal Health Informatics. View