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. 2020 Nov 18;22(11):e21329.
doi: 10.2196/21329.

Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis

Eisa Alanazi  1 , Abdulaziz Alashaikh  2 , Sarah Alqurashi  1 , Aued Alanazi  1
Affiliations
Free PMC article

Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis

Eisa Alanazi et al. J Med Internet Res. .
Free PMC article

Erratum in

Abstract

Background: A substantial amount of COVID-19-related data is generated by Twitter users every day. Self-reports of COVID-19 symptoms on Twitter can reveal a great deal about the disease and its prevalence in the community. In particular, self-reports can be used as a valuable resource to learn more about common symptoms and whether their order of appearance differs among different groups in the community. These data may be used to develop a COVID-19 risk assessment system that is tailored toward a specific group of people.

Objective: The aim of this study was to identify the most common symptoms reported by patients with COVID-19, as well as the order of symptom appearance, by examining tweets in Arabic.

Methods: We searched Twitter posts in Arabic for personal reports of COVID-19 symptoms from March 1 to May 27, 2020. We identified 463 Arabic users who had tweeted about testing positive for COVID-19 and extracted the symptoms they associated with the disease. Furthermore, we asked them directly via personal messaging to rank the appearance of the first 3 symptoms they had experienced immediately before (or after) their COVID-19 diagnosis. Finally, we tracked their Twitter timeline to identify additional symptoms that were mentioned within ±5 days from the day of the first tweet on their COVID-19 diagnosis. In total, 270 COVID-19 self-reports were collected, and symptoms were (at least partially) ranked.

Results: The collected self-reports contained 893 symptoms from 201 (74%) male and 69 (26%) female Twitter users. The majority (n=270, 82%) of the tracked users were living in Saudi Arabia (n=125, 46%) and Kuwait (n=98, 36%). Furthermore, 13% (n=36) of the collected reports were from asymptomatic individuals. Of the 234 users with symptoms, 66% (n=180) provided a chronological order of appearance for at least 3 symptoms. Fever (n=139, 59%), headache (n=101, 43%), and anosmia (n=91, 39%) were the top 3 symptoms mentioned in the self-reports. Additionally, 28% (n=65) reported that their COVID-19 experience started with a fever, 15% (n=34) with a headache, and 12% (n=28) with anosmia. Of the 110 symptomatic cases from Saudi Arabia, the most common 3 symptoms were fever (n=65, 59%), anosmia (n=46, 42%), and headache (n=42, 38%).

Conclusions: This study identified the most common symptoms of COVID-19 from tweets in Arabic. These symptoms can be further analyzed in clinical settings and may be incorporated into a real-time COVID-19 risk estimator.

Keywords: Arabic; COVID-19; Twitter; anosmia; health; informatics; social networks; symptom.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
A patient with COVID-19 tweets about how the loss of smell and taste was the only common symptom across all of their family members. The tweet was anonymized and translated into English.
Figure 2
Figure 2
Data collection steps.
Figure 3
Figure 3
Example of tweets collected within 5 days before or after the user tweeted about having a COVID-19–positive diagnosis.
Figure 4
Figure 4
Number of daily collected reports from Twitter (March to May 2020).
Figure 5
Figure 5
A comparison between symptom prevalence in our study and Sarker et al [5] (correlation coefficient=0.72).
See this image and copyright information in PMC

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