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

Natural Language Processing (692) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Cross-Sectional Studies in Public Health (278) Outbreak and Pandemic Preparedness and Management (1727) JMIR Theme Issue: COVID-19 Special Issue (2452) Infectious Diseases (non-STD/STI) (1575) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Infoveillance and Social Listening (209)

Published on in Vol 9, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27670, first published .
Social Media Monitoring of the COVID-19 Pandemic and Influenza Epidemic With Adaptation for Informal Language in Arabic Twitter Data: Qualitative Study

Social Media Monitoring of the COVID-19 Pandemic and Influenza Epidemic With Adaptation for Informal Language in Arabic Twitter Data: Qualitative Study

Social Media Monitoring of the COVID-19 Pandemic and Influenza Epidemic With Adaptation for Informal Language in Arabic Twitter Data: Qualitative Study

Authors of this article:

Lama Alsudias1, 2 Author Orcid Image ;   Paul Rayson2 Author Orcid Image
Article Authors Cited by (16) Tweetations (12) Metrics

Journals

  1. Qin Z, Ronchieri E. Exploring Pandemics Events on Twitter by Using Sentiment Analysis and Topic Modelling. Applied Sciences 2022;12(23):11924 View
  2. Athanasiou M, Fragkozidis G, Zarkogianni K, Nikita K. Long Short-term Memory–Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation. Journal of Medical Internet Research 2023;25:e42519 View
  3. Perenc L, Podgórska-Bednarz J, Guzik A, Drużbicki M. Impact of the COVID-19 Pandemic on the Level of Anxiety and Depression in Caregivers of Children Benefiting from Neurorehabilitation Services. International Journal of Environmental Research and Public Health 2023;20(5):4564 View
  4. Tian Y, Zhang W, Duan L, McDonald W, Osgood N. Comparison of pretrained transformer-based models for influenza and COVID-19 detection using social media text data in Saskatchewan, Canada. Frontiers in Digital Health 2023;5 View
  5. Sandu A, Ioanăș I, Delcea C, Geantă L, Cotfas L. Mapping the Landscape of Misinformation Detection: A Bibliometric Approach. Information 2024;15(1):60 View
  6. Nerella S, Bandyopadhyay S, Zhang J, Contreras M, Siegel S, Bumin A, Silva B, Sena J, Shickel B, Bihorac A, Khezeli K, Rashidi P. Transformers and large language models in healthcare: A review. Artificial Intelligence in Medicine 2024;154:102900 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. Al-Sarem M, Alsaeedi A, Saeed F, Boulila W, AmeerBakhsh O. A Novel Hybrid Deep Learning Model for Detecting COVID-19-Related Rumors on Social Media Based on LSTM and Concatenated Parallel CNNs. Applied Sciences 2021;11(17):7940 View
  9. Alasmari A, Addawood A, Nouh M, Rayes W, Al-Wabil A. A Retrospective Analysis of the COVID-19 Infodemic in Saudi Arabia. Future Internet 2021;13(10):254 View
  10. Alhazmi H. Arabic Twitter Conversation Dataset about the COVID-19 Vaccine. Data 2022;7(11):152 View
  11. Mourad A, Elbassuoni S. A large-scale analysis of COVID-19 tweets in the Arab region. Social Network Analysis and Mining 2022;12(1) View
  12. Al-Saif H, Al-Dossari H. Exploring the Role of Emotions in Arabic Rumor Detection in Social Media. Applied Sciences 2023;13(15):8815 View
  13. Abdelhady N, Elsemman I, Farghally M, Soliman T. Developing Analytical Tools for Arabic Sentiment Analysis of COVID-19 Data. Algorithms 2023;16(7):318 View

Books/Policy Documents

  1. Sarker A. Natural Language Processing in Biomedicine. View