2020
DOI: 10.2196/preprints.26446
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Correction: Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis (Preprint)

Abstract: UNSTRUCTURED REMOVE

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 0 publications
0
1
0
Order By: Relevance
“…While our work focused on analyzing the contents of governmental messages on Twitter as they relate to disease or non-disease related topics, previous notable work focused on either disease or non-disease-related topics [ 8 , 28 ]. Other researchers specifically explored the type of symptoms experienced by patients with COVID-19 by analyzing public conversations posted on Twitter [ 29 , 30 ]. Our findings have shown the interconnections between these two topic groups, which is similar to the findings of a recent study that examined public concerns during the COVID-19 pandemic in Saudi [ 15 ].…”
Section: Discussionmentioning
confidence: 99%
“…While our work focused on analyzing the contents of governmental messages on Twitter as they relate to disease or non-disease related topics, previous notable work focused on either disease or non-disease-related topics [ 8 , 28 ]. Other researchers specifically explored the type of symptoms experienced by patients with COVID-19 by analyzing public conversations posted on Twitter [ 29 , 30 ]. Our findings have shown the interconnections between these two topic groups, which is similar to the findings of a recent study that examined public concerns during the COVID-19 pandemic in Saudi [ 15 ].…”
Section: Discussionmentioning
confidence: 99%