ArticleInternational journal of environmental research and public health2020
A Sentiment Analysis Approach to Predict an Individual's Awareness of the Precautionary Procedures to Prevent COVID-19 Outbreaks in Saudi Arabia.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- A Data Centric HitL Framework for Conducting aSsystematic Error Analysis of NLP Datasets using Explainable AI.Scientific reports · 2025Article
- Soft computing analysis of the factors associated with stress, anxiety, and depression.BMC public health · 2025Article
- A hybrid dependency-based approach for Urdu sentiment analysis.Scientific reports · 2023Article
- Article
- COVID-19 vaccine rejection causes based on Twitter people's opinions analysis using deep learning.Social network analysis and mining · 2023Article
- Comparison of pretrained transformer-based models for influenza and COVID-19 detection using social media text data in Saskatchewan, Canada.Frontiers in digital health · 2023Article
- COVID-19 Public Opinion: A Twitter Healthcare Data Processing Using Machine Learning Methodologies.International journal of environmental research and public health · 2022Article
- Leveraging Tweets for Artificial Intelligence Driven Sentiment Analysis on the COVID-19 Pandemic.Healthcare (Basel, Switzerland) · 2022Article
- A machine learning-based approach for sentiment analysis on distance learning from Arabic Tweets.PeerJ. Computer science · 2022Article
- A Hybrid Feature Extraction Method for Nepali COVID-19-Related Tweets Classification.Computational intelligence and neuroscience · 2022Article
- Rapid assessment of communication consistency: sentiment analysis of public health briefings during the COVID-19 pandemic.AIMS public health · 2022Article
- COVID-19 and Saudi Arabia: Awareness, Attitude, and Practice.Journal of multidisciplinary healthcare · 2022Review
- TClustVID: A novel machine learning classification model to investigate topics and sentiment in COVID-19 tweets.Knowledge-based systems · 2021Article
- Analyzing Twitter Data to Evaluate People's Attitudes towards Public Health Policies and Events in the Era of COVID-19.International journal of environmental research and public health · 2021Article
- Deep Learning-Based Methods for Sentiment Analysis on Nepali COVID-19-Related Tweets.Computational intelligence and neuroscience · 2021Article
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Authors and funding
8 authors.
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Abstract
In March 2020, the World Health Organization (WHO) declared the outbreak of Coronavirus disease 2019 (COVID-19) as a pandemic, which affected all countries worldwide. During the outbreak, public sentiment analyses contributed valuable information toward making appropriate public health responses. This study aims to develop a model that predicts an individual's awareness of the precautionary procedures in five main regions in Saudi Arabia. In this study, a dataset of Arabic COVID-19 related tweets was collected, which fell in the period of the curfew. The dataset was processed, based on several machine learning predictive models: Support Vector Machine (SVM), K-nearest neighbors (KNN), and Naïve Bayes (NB), along with the N-gram feature extraction technique. The results show that applying the SVM classifier along with bigram in Term Frequency-Inverse Document Frequency (TF-IDF) outperformed other models with an accuracy of 85%. The results of awareness prediction showed that the south region observed the highest level of awareness towards COVID-19 containment measures, whereas the middle region was the least. The proposed model can support the medical sectors and decision-makers to decide the appropriate procedures for each region based on their attitudes towards the pandemic.
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