Version 1
: Received: 31 March 2020 / Approved: 3 April 2020 / Online: 3 April 2020 (11:45:33 CEST)
How to cite:
Alhajji, M.; Al Khalifah, A.; Aljubran, M.; Alkhalifah, M. Sentiment Analysis of Tweets in Saudi Arabia Regarding Governmental Preventive Measures to Contain COVID-19. Preprints2020, 2020040031. https://doi.org/10.20944/preprints202004.0031.v1
Alhajji, M.; Al Khalifah, A.; Aljubran, M.; Alkhalifah, M. Sentiment Analysis of Tweets in Saudi Arabia Regarding Governmental Preventive Measures to Contain COVID-19. Preprints 2020, 2020040031. https://doi.org/10.20944/preprints202004.0031.v1
Alhajji, M.; Al Khalifah, A.; Aljubran, M.; Alkhalifah, M. Sentiment Analysis of Tweets in Saudi Arabia Regarding Governmental Preventive Measures to Contain COVID-19. Preprints2020, 2020040031. https://doi.org/10.20944/preprints202004.0031.v1
APA Style
Alhajji, M., Al Khalifah, A., Aljubran, M., & Alkhalifah, M. (2020). Sentiment Analysis of Tweets in Saudi Arabia Regarding Governmental Preventive Measures to Contain COVID-19. Preprints. https://doi.org/10.20944/preprints202004.0031.v1
Chicago/Turabian Style
Alhajji, M., Mohammed Aljubran and Mohammed Alkhalifah. 2020 "Sentiment Analysis of Tweets in Saudi Arabia Regarding Governmental Preventive Measures to Contain COVID-19" Preprints. https://doi.org/10.20944/preprints202004.0031.v1
Abstract
Background: Countries around the world are facing extraordinary challenges in implementing various measures to slow down the spread of the novel coronavirus (COVID-19). Guided by international recommendations, Saudi Arabia has implemented a series of infection control measures after the detection of the first confirmed case in the country. However, in order for these measures to be effective, public attitudes and compliance must be conducive as perceived risk is strongly associated with health behaviors. The primary objective of this study is to assess Saudis’ attitudes towards COVID-19 preventive measures to guide future health communication content. Methods: Naïve Bayes machine learning model was used to run Arabic sentiment analysis of Twitter posts through the Natural Language Toolkit (NLTK) library in Python. Tweets containing hashtags pertaining to seven public health measures imposed by the government were collected and analyzed. Results: A total of 53,127 tweets were analyzed. All measures, except one, showed more positive tweets than negative. Measures that pertain to religious practices showed the most positive sentiment. Discussion: Saudi Twitter users showed support and positive attitudes towards the infection control measures to combat COVID-19. It is postulated that this conducive public response is reflective of the overarching, longstanding popular confidence in the government. Religious notions may also play a positive role in preparing believers at times of crises. Findings of this study broadened our understanding to develop proper public health messages and promote stronger compliance with control measures to control COVID-19.
Keywords
Saudi Arabia, COVID-19, Sentiment Analysis, Twitter, Measures
Subject
Public Health and Healthcare, Health Policy and Services
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
