Mining twitter to explore the emergence of COVID-19 symptoms.
Public Health Nurs
; 37(6): 934-940, 2020 11.
Article
in English
| MEDLINE | ID: covidwho-767629
ABSTRACT
BACKGROUND:
The Centers for Disease Control and Prevention (CDC) in United States initially alerted the public to three COVID-19 signs and symptoms-fever, dry cough, and shortness of breath. Concurrent social media posts reflected a wider range of symptoms of COVID-19 besides these three symptoms. Because social media data have a potential application in the early identification novel virus symptoms, this study aimed to explore what symptoms mentioned in COVID-19-related social media posts during the early stages of the pandemic.METHODS:
We collected COVID-19-related Twitter tweets posted in English language between March 30, 2020 and April 19, 2020 using search terms of COVID-19 synonyms and three common COVID-19 symptoms suggested by the CDC in March. Only unique tweets were extracted for analysis of symptom terms.RESULTS:
A total of 36 symptoms were extracted from 30,732 unique tweets. All the symptoms suggested by the CDC for COVID-19 screening in March, April, and May were mentioned in tweets posted during the early stages of the pandemic.DISCUSSION:
The findings of this study revealed that many COVID-19-related symptoms mentioned in Twitter tweets earlier than the announcement by the CDC. Monitoring social media data is a promising approach to public health surveillance.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Data Mining
/
Social Media
/
Public Health Surveillance
/
COVID-19
Type of study:
Observational study
/
Reviews
Limits:
Humans
Country/Region as subject:
North America
Language:
English
Journal:
Public Health Nurs
Year:
2020
Document Type:
Article
Affiliation country:
Phn.12809
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