Dana Wehbe
ABSTRACT
This research project predicts and infers real-time insights on public mental health relevant to education during and after the COVID-19 pandemic by modeling, deploying, and testing an end-to-end spatiotemporal sentiment analysis framework. Moreover, the project aims to analyze the sentiments and emotions of the public; from Twitter, toward the current context of the e-learning process factored by aspects and emotions. The framework consists of four predictive models based on statistical analysis and machine learning to analyze the UAE education-related Twitter dataset. The first analytics is spatiotemporal analytics, which describes an event at a specific time and specific location. Spatiotemporal analytics is used as the base for the remaining three analytics: Aspect-based Sentiment Analysis, sentiment analysis, and emotion analysis. Aspect-based Sentiment Analysis considers the words/terms related to relevant aspects and then identify the sentiment associated with them. Sentiment Analysis is used to extract the sentiment in a specific text. Emotion Analysis identifies the type of emotion felt by users in their tweets. All the analytics will be visualized into a responsive website that provides a prompt understanding of the public opinions and their feedback towards the e-learning process. As a result, a group of recommendations is generated based on the analytics’ resulting emotion to enhance the mental health.
- M. O. E. Website, "One million students of government and private schools resume classes today as new academic Year 2019-2020 begins.," Ministry of Education, [Online]. Available: https://www.moe.gov.ae/En/MediaCenter/News/Pages/ooltoday2019.aspx. [Accessed 17 April 2021].Google Scholar
- M. O. E. Website, "Distance learning system to continue to be applied till end of current academic year," [Online]. Available: https://www.moe.gov.ae/En/MediaCenter/News/Pages/elearning3.aspx. [Accessed 17 April 2021].Google Scholar
- G. M. I. Blogger, "UAE SOCIAL MEDIA USAGE STATISTICS," 2020. [Online]. Available: https://www.globalmediainsight.com/blog/uae-social-media-statistics/. [Accessed 17 April 2021].Google Scholar
- A. Alqahtani and A. Rajkhan, "E-Learning Critical Success Factors during the COVID-19 Pandemic: A Comprehensive Analysis of E-Learning Managerial Perspectives," Education Sciences, 2020.Google Scholar
- N. Brown, K. Te Riele, B. Shelley and J. Woodroffe, "Learning at home during COVID-19: Effects on vulnerable young Australians," Independent Rapid Response Report, 2020.Google Scholar
- M. O. Edeh, "Impact of Coronavirus Pandemic on Education," Journal of Education and Practice, 2020.Google Scholar
- N. Kaur, D. Dwivedi, J. Arora and A. Gandhi, "Study of the effectiveness of e-learning to conventional teaching in medical undergraduates amid COVID-19 pandemic.," Natl J Physiol Pharm Pharmacol, 2020.Google Scholar
- R. Moawad, "Online Learning during the COVID- 19 Pandemic and Academic Stress in University Students," Revista Romaneasca pentru Educatie Multidimensionala,12(1Sup2), 2020.Google Scholar
- N. Kapasia, P. Paul, A. Roy, J. Saha, A. Zaveri, R. Mallick, B. Barman, P. Das and P. Chou, "Impact of lockdown on learning status of undergraduate and postgraduate students during COVID-19 pandemic in West Bengal, India," Children and Youth Services Review, vol. 116, 2020.Google ScholarCross Ref
- S. Dhawan, "Online Learning: A Panacea in the Time of COVID-19 Crisis," Journal of Educational Technology Systems, vol. 49, 2020.Google ScholarCross Ref
- S. Agarwal and J. Dewan, "An Analysis of the Effectiveness of Online Learning in Colleges of Uttar Pradesh during the COVID 19 Lockdown," Journal of Xi'an University of Architecture & Technology, vol. XII, no. V.Google Scholar
- C. Tartavulea, C. Albu, N. Albu, R. Dieaconescu and S. Petre, "Online Teaching Practices and the Effectiveness of the Educational Process in the Wake of the COVID-19 Pandemic," Amfiteatru Economic, 2020.Google Scholar
- W. Kidd and J. Murray, "The Covid-19 pandemic and its effects on teacher education in England: how teacher educators moved practicum learning online," European Journal of Teacher Education, 2020.Google Scholar
Index Terms
- UAE e-Learning Sentiment Analysis Framework
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