Content analysis of Persian/Farsi Tweets during COVID-19 pandemic in Iran using NLP

Pedram Hosseini, Poorya Hosseini, David Broniatowski

Abstract
Iran, along with China, South Korea, and Italy was among the countries that were hit hard in the first wave of the COVID-19 spread. Twitter is one of the widely-used online platforms by Iranians inside and abroad for sharing their opinion, thoughts, and feelings about a wide range of issues. In this study, using more than 530,000 original tweets in Persian/Farsi on COVID-19, we analyzed the topics discussed among users, who are mainly Iranians, to gauge and track the response to the pandemic and how it evolved over time. We applied a combination of manual annotation of a random sample of tweets and topic modeling tools to classify the contents and frequency of each category of topics. We identified the top 25 topics among which living experience under home quarantine emerged as a major talking point. We additionally categorized the broader content of tweets that shows satire, followed by news, is the dominant tweet type among Iranian users. While this framework and methodology can be used to track public response to ongoing developments related to COVID-19, a generalization of this framework can become a useful framework to gauge Iranian public reaction to ongoing policy measures or events locally and internationally.
Anthology ID:
2020.nlpcovid19-2.26
Volume:
Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
Month:
December
Year:
2020
Address:
Online
Editors:
Karin Verspoor, Kevin Bretonnel Cohen, Michael Conway, Berry de Bruijn, Mark Dredze, Rada Mihalcea, Byron Wallace
Venue:
NLP-COVID19
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
Language:
URL:
https://aclanthology.org/2020.nlpcovid19-2.26
DOI:
10.18653/v1/2020.nlpcovid19-2.26
Bibkey:
Cite (ACL):
Pedram Hosseini, Poorya Hosseini, and David Broniatowski. 2020. Content analysis of Persian/Farsi Tweets during COVID-19 pandemic in Iran using NLP. In Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020, Online. Association for Computational Linguistics.
Cite (Informal):
Content analysis of Persian/Farsi Tweets during COVID-19 pandemic in Iran using NLP (Hosseini et al., NLP-COVID19 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/2020.nlpcovid19-2.26.pdf
Code
 phosseini/COVID19-fa
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