Cargando…
eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis
Understanding social media networks and group interactions is crucial to the advancement of linguistic and cultural behavior. This includes how people accessed advice on health during COVID-19 lockdown. Some people turned to social media to access information on health when other routes were curtail...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032816/ https://www.ncbi.nlm.nih.gov/pubmed/35457483 http://dx.doi.org/10.3390/ijerph19084615 |
_version_ | 1784692737900019712 |
---|---|
author | Hermann, Caroll Govender, Melanie |
author_facet | Hermann, Caroll Govender, Melanie |
author_sort | Hermann, Caroll |
collection | PubMed |
description | Understanding social media networks and group interactions is crucial to the advancement of linguistic and cultural behavior. This includes how people accessed advice on health during COVID-19 lockdown. Some people turned to social media to access information on health when other routes were curtailed by isolation rules, particularly among older generations. Facebook public pages, groups and verified profiles using keywords “senior citizen health”, “older generations”, and “healthy living” were analyzed over a 12-month period to examine engagement with social media promoting good mental health. CrowdTangle was used to source status updates, photo and video sharing information in the English language, which resulted in an initial 116,321 posts and 6,462,065 interactions. Data analysis and visualization were used to explore large datasets, including natural language processing for “message” content discovery, word frequency and correlational analysis as well as co-word clustering. Preliminary results indicate strong links to healthy aging information shared on social media, which showed correlations to global daily confirmed cases and daily deaths. The results can identify public concerns early on and address mental health issues among senior citizens on Facebook. |
format | Online Article Text |
id | pubmed-9032816 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90328162022-04-23 eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis Hermann, Caroll Govender, Melanie Int J Environ Res Public Health Article Understanding social media networks and group interactions is crucial to the advancement of linguistic and cultural behavior. This includes how people accessed advice on health during COVID-19 lockdown. Some people turned to social media to access information on health when other routes were curtailed by isolation rules, particularly among older generations. Facebook public pages, groups and verified profiles using keywords “senior citizen health”, “older generations”, and “healthy living” were analyzed over a 12-month period to examine engagement with social media promoting good mental health. CrowdTangle was used to source status updates, photo and video sharing information in the English language, which resulted in an initial 116,321 posts and 6,462,065 interactions. Data analysis and visualization were used to explore large datasets, including natural language processing for “message” content discovery, word frequency and correlational analysis as well as co-word clustering. Preliminary results indicate strong links to healthy aging information shared on social media, which showed correlations to global daily confirmed cases and daily deaths. The results can identify public concerns early on and address mental health issues among senior citizens on Facebook. MDPI 2022-04-12 /pmc/articles/PMC9032816/ /pubmed/35457483 http://dx.doi.org/10.3390/ijerph19084615 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hermann, Caroll Govender, Melanie eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis |
title | eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis |
title_full | eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis |
title_fullStr | eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis |
title_full_unstemmed | eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis |
title_short | eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis |
title_sort | ehealth engagement on facebook during covid-19: simplistic computational data analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9032816/ https://www.ncbi.nlm.nih.gov/pubmed/35457483 http://dx.doi.org/10.3390/ijerph19084615 |
work_keys_str_mv | AT hermanncaroll ehealthengagementonfacebookduringcovid19simplisticcomputationaldataanalysis AT govendermelanie ehealthengagementonfacebookduringcovid19simplisticcomputationaldataanalysis |