UAE e-learning sentiment analysis framework
7th International Conference on Arab Women in Computing, ArabWIC 2021
; 2021.
Article
in English
| Scopus | ID: covidwho-1592637
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. Aspectbased 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. © 2021 Association for Computing Machinery.
Aspect-based, Sentiment, Analysis; COVID-19; Data, mining; Education; ELearning; Emotions, Analysis; Parents; Recommendation, engine; Sentiments, Analysis; Students; Twitter; UAE; E-learning; Education, computing; Learning, systems; Predictive, analytics; Recommender, systems; Sentiment, analysis; Analysis, frameworks; Aspect-based, sentiment, analyse; E, -, learning; Emotion, analysis; Mental, health; Parent; Social, networking, (online)
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
7th International Conference on Arab Women in Computing, ArabWIC 2021
Year:
2021
Document Type:
Article
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