Your browser doesn't support javascript.
Experiencing Stress During COVID-19: A Computational Analysis of Stressors and Emotional Responses to Stress.
Kang, Jiwon; Kim, Jieun; Kim, Taenyun; Song, Hayeon; Han, Jinyoung.
  • Kang J; Department of Applied Artificial Intelligence, Sungkyunkwan University, Jongno-gu, Seoul, Republic of Korea.
  • Kim J; Department of Human-AI Interaction, and Sungkyunkwan University, Jongno-gu, Seoul, Republic of Korea.
  • Kim T; Department of Interaction Science, Sungkyunkwan University, Jongno-gu, Seoul, Republic of Korea.
  • Song H; Department of Human-AI Interaction, and Sungkyunkwan University, Jongno-gu, Seoul, Republic of Korea.
  • Han J; Department of Applied Artificial Intelligence, Sungkyunkwan University, Jongno-gu, Seoul, Republic of Korea.
Cyberpsychol Behav Soc Netw ; 25(9): 561-570, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2028987
ABSTRACT
This study aims to unveil how COVID-19 affected the experience of stress by focusing on the stressors. Using computational analysis based on a newly developed stressor identification model, we compared the experience of stress expressed by Korean Twitter users before and during the pandemic in terms of (1) the stressors as the source of stress and (2) emotion as the manifestation of stress. Both tweet-level (N = 202,556) and user-level (N = 24,803) analyses revealed that social factors are prevalent sources of stress both before and during the pandemic. Moreover, social stressors increased the most during the pandemic. While stress from social stressors was manifested mainly as sadness before the pandemic, anger became the predominant emotional manifestation during the pandemic. Public health policies and educators should consider social stressors as the predominant source of stress during the pandemic and seek ways to prepare the public better for such threats.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Qualitative research Topics: Long Covid Limits: Humans Language: English Journal: Cyberpsychol Behav Soc Netw Journal subject: Behavioral Sciences / Psychology Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Qualitative research Topics: Long Covid Limits: Humans Language: English Journal: Cyberpsychol Behav Soc Netw Journal subject: Behavioral Sciences / Psychology Year: 2022 Document Type: Article