Golz, C; Richter, D; Sprecher, N; Gurtner, C (2022). Mental health-related communication in a virtual community: text mining analysis of a digital exchange platform during the Covid-19 pandemic. BMC psychiatry, 22(1), p. 430. BioMed Central 10.1186/s12888-022-04080-1
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BACKGROUND
Virtual communities played an important role in mental health and well-being during the Covid-19 pandemic by providing access to others and thereby preventing loneliness. The pandemic has accelerated the urge for digital solutions for people with pre-existing mental health problems. So far, it remains unclear how the people concerned communicate with each other and benefit from peer-to-peer support on a moderated digital platform.
OBJECTIVE
The aim of the project was to identify and describe the communication patterns and verbal expression of users on the inCLOUsiv platform during the first lockdown in 2020.
METHODS
Discussions in forums and live chats on inCLOUsiv were analysed using text mining, which included frequency, correlation, n-gram and sentiment analyses.
RESULTS
The communication behaviour of users on inCLOUsiv was benevolent and supportive; and 72% of the identified sentiments were positive. Users addressed the topics of 'corona', 'anxiety' and 'crisis' and shared coping strategies.
CONCLUSIONS
The benevolent interaction between users on inCLOUsiv is in line with other virtual communities for Covid-19 and the potential for peer-to-peer support. Users can benefit from each other's experiences and support each other. Virtual communities can be used as an adjuvant to existing therapy, particularly in times of reduced access to local health services.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > University Psychiatric Services > Department of Nursing and Education |
UniBE Contributor: |
Richter, Dirk |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1471-244X |
Publisher: |
BioMed Central |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
27 Jun 2022 07:29 |
Last Modified: |
05 Dec 2022 16:21 |
Publisher DOI: |
10.1186/s12888-022-04080-1 |
PubMed ID: |
35752758 |
Uncontrolled Keywords: |
Covid-19 Mental health Sentiment analysis Text mining Virtual communities |
BORIS DOI: |
10.48350/170939 |
URI: |
https://boris.unibe.ch/id/eprint/170939 |
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