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Identifying Silver Linings During the Pandemic Through Natural Language Processing.

Juan Antonio Lossio-Ventura1,2, Angela Yuson Lee3, Jeffrey T Hancock3

  • 1Department of Dermatology, Stanford University, Stanford, CA, United States.

Frontiers in Psychology
|September 20, 2021
PubMed
Summary

The COVID-19 pandemic increased mental distress, but people found hope through community, gratitude, and belief in positive social change. Identifying these "silver linings" can bolster resilience against future health crises.

Keywords:
COVID-19natural language processingprotective factorssentiment analysissilver liningstopic modeling

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Area of Science:

  • Psychology
  • Public Health
  • Computational Linguistics

Background:

  • The COVID-19 pandemic significantly impacted global mental health, leading to increased depression and psychological distress.
  • Identifying sources of hope and consolation is crucial for supporting individual well-being during crises.

Purpose of the Study:

  • To identify positive aspects or "silver linings" experienced by individuals during the COVID-19 pandemic.
  • To explore sources of strength that facilitated perseverance through the crisis.

Main Methods:

  • Employed computational natural language processing (NLP) methods.
  • Conducted qualitative thematic content analysis to identify emergent themes.

Main Results:

  • Key "silver linings" included finding a sense of community and closeness.
  • Gratitude and belief in the potential for positive social change emerged as significant coping mechanisms.
  • These findings highlight the importance of benefit-finding and protective factors.

Conclusions:

  • Public health policy can leverage identified sources of strength to enhance societal resilience.
  • Interventions focusing on community, gratitude, and positive social change can mitigate pandemic-related distress.
  • This research offers insights for preparedness and response to future health crises.