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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jan 10, 2021
Open Peer Review Period: Jan 10, 2021 - Mar 7, 2021
Date Accepted: Mar 1, 2021
Date Submitted to PubMed: Mar 4, 2021
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Temporal Dynamics of Public Emotions During the COVID-19 Pandemic at the Epicenter of the Outbreak: Sentiment Analysis of Weibo Posts From Wuhan

Yu S, Eisenman D, Han Z

Temporal Dynamics of Public Emotions During the COVID-19 Pandemic at the Epicenter of the Outbreak: Sentiment Analysis of Weibo Posts From Wuhan

J Med Internet Res 2021;23(3):e27078

DOI: 10.2196/27078

PMID: 33661755

PMCID: 7977613

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Temporal Dynamics of Emotions during the COVID-19 Pandemic at the Center of Outbreak: A Sentimental Analysis of Weibo Tweets from Wuhan

  • Shaobin Yu; 
  • David Eisenman; 
  • Ziqiang Han

ABSTRACT

Background:

The ongoing COVID-19 pandemic increased the general public's anxiety, depression, post-traumatic stress disorder (PTSD), psychological stress in various degrees around the world.

Objective:

This study aims to detect the temporal patterns of emotional fluctuation, the significant events that affected the emotional changes and variations, and the hourly variations of the emotions within a day.

Methods:

Based on a longitudinal dataset of 816,556 posts tweeted by 27,912 Weibo users in Wuhan from December 31, 2019 to April 31, 2020, we processed general sentiment inclination rating and the type of sentiments of Weibo tweets by relevant Python libraries and the Naive Bayes Classifier algorithm. We also grouped the hours into five-time groups to measure the netizens’ sentimental changes during different periods in a day.

Results:

Overall, negative emotions like surprise, fear, and anger are the salient emotions on the social media platform. Milestone events, such as the confirmation of human-to-human transmission, etc., are the primary events that ignited the emotions. Emotions varied within a day. Although all emotions are more prevalent in the afternoon and night, fear and anger are more dominant in the morning and afternoon, while depression is more salient during the night.

Conclusions:

Milestone events during the pandemic are the primary events that ignited the citizens’ emotions. In addition, the emotions varied within a day. Better-tailored mental health services and interventions could be conducted accordingly.


 Citation

Please cite as:

Yu S, Eisenman D, Han Z

Temporal Dynamics of Public Emotions During the COVID-19 Pandemic at the Epicenter of the Outbreak: Sentiment Analysis of Weibo Posts From Wuhan

J Med Internet Res 2021;23(3):e27078

DOI: 10.2196/27078

PMID: 33661755

PMCID: 7977613

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