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Topic Discovery on Farsi, English, French, and Arabic Tweets Related to COVID-19 Using Text Mining Techniques
Hamoon Jafarian, Mahin Mohammadi, Alireza Javaheri, Makram Sukarieh, Mohsen Yoosefi Nejad, Abbas Sheikhtaheri, Mehdi Hosseinzadeh, Elaheh Momeni-Ortner, Reza Rawassizadeh
26 - 33
10.3233/SHTI210084
Research Article
Studies in Health Technology and Informatics
Volume 279: Navigating Healthcare Through Challenging Times
Abstract

Background:

Social networks are a good source for monitoring public health during the outbreak of COVID-19, these networks play an important role in identifying useful information.

Objectives:

This study aims to draw a comparison of the public’s reaction in Twitter among the countries of West Asia (a.k.a Middle East) and North Africa in order to make an understanding of their response regarding the same global threat.

Methods:

766,630 tweets in four languages (Arabic, English French, and Farsi) tweeted in March 2020, were investigated.

Results:

The results indicate that the only common theme among all languages is “government responsibilities (political)” which indicates the importance of this subject for all nations.

Conclusion:

Although nations react similarly in some aspects, they respond differently in others and therefore, policy localization is a vital step in confronting problems such as COVID-19 pandemic.

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