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

JMIR Theme Issue: COVID-19 Special Issue (2458) Natural Language Processing (704) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1660) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Outbreak and Pandemic Preparedness and Management (1740) Machine Learning (1491) Artificial Intelligence (1409) Infodemiology and Infoveillance (1365) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (385) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1049) Infectious Diseases (non-STD/STI) (1588) Hygiene and Infection Prevention (324) Anxiety and Stress Disorders (1074)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27341, first published .
Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Authors of this article:

Achini Adikari1 Author Orcid Image ;   Rashmika Nawaratne1 Author Orcid Image ;   Daswin De Silva1 Author Orcid Image ;   Sajani Ranasinghe1 Author Orcid Image ;   Oshadi Alahakoon2 Author Orcid Image ;   Damminda Alahakoon1 Author Orcid Image
Article Authors Cited by (33) Tweetations (10) Metrics

Journals

  1. Adikari A, Burnett D, Sedera D, de Silva D, Alahakoon D. Value co-creation for open innovation: An evidence-based study of the data driven paradigm of social media using machine learning.. International Journal of Information Management Data Insights 2021;1(2):100022 View
  2. De Silva D, Alahakoon D. An artificial intelligence life cycle: From conception to production. Patterns 2022;3(6):100489 View
  3. Zhou Y, Li R, Shen L. Targeting COVID-19 vaccine-hesitancy in college students: An audience-centered approach. Journal of American College Health 2024;72(9):3526 View
  4. He G, Zhang Y. (Im)mobility and performance of emotions: Chinese international students’ difficult journeys to home during the COVID-19 pandemic. Mobile Media & Communication 2023;11(2):248 View
  5. Herman A, Zaremba D, Kossowski B, Marchewka A. The utility of the emBODY tool as a novel method of studying complex phenomena-related emotions. Scientific Reports 2022;12(1) View
  6. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L. Measuring the Impact of Language Models in Sentiment Analysis for Mexico’s COVID-19 Pandemic. Electronics 2022;11(16):2483 View
  7. Chamishka S, Madhavi I, Nawaratne R, Alahakoon D, De Silva D, Chilamkurti N, Nanayakkara V. A voice-based real-time emotion detection technique using recurrent neural network empowered feature modelling. Multimedia Tools and Applications 2022;81(24):35173 View
  8. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L, Pareja Lora A, Ochoa Ruiz G, Hošovský A. Monitoring the Emotional Response to the COVID-19 Pandemic Using Sentiment Analysis: A Case Study in Mexico. Computational Intelligence and Neuroscience 2022;2022:1 View
  9. Xiong Y, Hong H, Liu C, Zhang Y. Social isolation and the brain: effects and mechanisms. Molecular Psychiatry 2023;28(1):191 View
  10. Hu M, Conway M. Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia. JMIR Infodemiology 2022;2(2):e36941 View
  11. He S, Li D, Liu C, Xiong Y, Liu D, Feng J, Wen J, Napoli C. Crisis communication in the WHO COVID-19 press conferences: A retrospective analysis. PLOS ONE 2023;18(3):e0282855 View
  12. Shin W, Wang W, Song J. COVID-racism on social media and its impact on young Asians in Australia. Asian Journal of Communication 2023;33(3):228 View
  13. Lukkahatai N, Rodney T, Ling C, Daniel B, Han H. Long COVID in the context of social determinants of health. Frontiers in Public Health 2023;11 View
  14. Mitre-Hernandez H, Ferro-Perez R, Cardona-Reyes H, Lara-Alvarez C. Detecting Emotional States from Video to Improve the Electronic Patient Record. SSRN Electronic Journal 2022 View
  15. Dupuy-Zini A, Audeh B, Gérardin C, Duclos C, Gagneux-Brunon A, Bousquet C. Users’ Reactions to Announced Vaccines Against COVID-19 Before Marketing in France: Analysis of Twitter Posts. Journal of Medical Internet Research 2023;25:e37237 View
  16. Weerasinghe S, Oyebode O, Orji R, Matwin S. Dynamics of emotion trends in Canadian Twitter users during COVID-19 confinement in relation to caseloads: Artificial intelligence-based emotion detection approach. DIGITAL HEALTH 2023;9 View
  17. Zolnoori M, Vergez S, Sridharan S, Zolnour A, Bowles K, Kostic Z, Topaz M. Is the patient speaking or the nurse? Automatic speaker type identification in patient–nurse audio recordings. Journal of the American Medical Informatics Association 2023;30(10):1673 View
  18. Li Y. The phenomenon of political trust in virtual communities (based on the materials of Chinese social networks during the Covid-19 pandemic). Communicology 2023;11(4):13 View
  19. Chandrasekaran R, Konaraddi K, Sharma S, Moustakas E. Text-Mining and Video Analytics of COVID-19 Narratives Shared by Patients on YouTube. Journal of Medical Systems 2024;48(1) View
  20. Mou X, Peng Q, Sun Z, Bashir M, Li H. Multi-document influence on readers: augmenting social emotion prediction by learning document interactions. Neural Computing and Applications 2024;36(12):6701 View
  21. Pallewela N, Alahakoon D, Adikari A, Pierce J, Rose M. Optimizing Speech Emotion Recognition with Machine Learning Based Advanced Audio Cue Analysis. Technologies 2024;12(7):111 View
  22. Gamage G, De Silva D, Mills N, Alahakoon D, Manic M. Emotion AWARE: an artificial intelligence framework for adaptable, robust, explainable, and multi-granular emotion analysis. Journal of Big Data 2024;11(1) View
  23. Qin S, Chislett B, Ischia J, Ranasinghe W, de Silva D, Coles‐Black J, Woon D, Bolton D. ChatGPT and generative AI in urology and surgery—A narrative review. BJUI Compass 2024 View
  24. Bamford S, Gardner W, Winkler D, Muir B, Alahakoon D, Pigram P. Self-Organizing Maps for Secondary Ion Mass Spectrometry. Journal of the American Society for Mass Spectrometry 2024;35(10):2516 View
  25. Xie Q, Wu H, Zhang R. Using online negative emotions to predict risk-coping behaviors in the relocation of Beijing municipal government. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Ruiz R, Velásquez J. Artificial Intelligence and Machine Learning for Healthcare. View
  2. Kaur J, Patel S, Vasani M, Saini J. Advances in Information Communication Technology and Computing. View
  3. Ahuja K. Emotional AI and Human-AI Interactions in Social Networking. View