Understanding Social Support Expressed in a COVID-19 Online Forum

Anietie Andy, Brian Chu, Ramie Fathy, Barrington Bennett, Daniel Stokes, Sharath Chandra Guntuku


Abstract
In online forums focused on health and wellbeing, individuals tend to seek and give the following social support: emotional and informational support. Understanding the expressions of these social supports in an online COVID- 19 forum is important for: (a) the forum and its members to provide the right type of support to individuals and (b) determining the long term effects of the COVID-19 pandemic on the well-being of the public, thereby informing interventions. In this work, we build four machine learning models to measure the extent of the following social supports expressed in each post in a COVID-19 online forum: (a) emotional support given (b) emotional support sought (c) informational support given, and (d) informational support sought. Using these models, we aim to: (i) determine if there is a correlation between the different social supports expressed in posts e.g. when members of the forum give emotional support in posts, do they also tend to give or seek informational support in the same post? (ii) determine how these social supports sought and given changes over time in published posts. We find that (i) there is a positive correlation between the informational support given in posts and the emotional support given and emotional support sought, respectively, in these posts and (ii) over time, users tended to seek more emotional support and give less emotional support.
Anthology ID:
2021.louhi-1.3
Volume:
Proceedings of the 12th International Workshop on Health Text Mining and Information Analysis
Month:
April
Year:
2021
Address:
online
Venues:
EACL | Louhi
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
19–27
Language:
URL:
https://aclanthology.org/2021.louhi-1.3
DOI:
Bibkey:
Cite (ACL):
Anietie Andy, Brian Chu, Ramie Fathy, Barrington Bennett, Daniel Stokes, and Sharath Chandra Guntuku. 2021. Understanding Social Support Expressed in a COVID-19 Online Forum. In Proceedings of the 12th International Workshop on Health Text Mining and Information Analysis, pages 19–27, online. Association for Computational Linguistics.
Cite (Informal):
Understanding Social Support Expressed in a COVID-19 Online Forum (Andy et al., Louhi 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.louhi-1.3.pdf