Cargando…
Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach
ADRD caregivers increasingly use social media to meet their health information wants (HIW). Machine learning (ML) tools may help understand caregivers’ HIW as expressed via social media. This pilot study explored a collaborative, iterative process between domain experts and ML tools to identify ADRD...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7742928/ http://dx.doi.org/10.1093/geroni/igaa057.2261 |
_version_ | 1783624101437374464 |
---|---|
author | Xie, Bo Wang, Zhendong Zou, Ning Luo, Zhimeng Hilsabeck, Robin Aguirre, Alyssa |
author_facet | Xie, Bo Wang, Zhendong Zou, Ning Luo, Zhimeng Hilsabeck, Robin Aguirre, Alyssa |
author_sort | Xie, Bo |
collection | PubMed |
description | ADRD caregivers increasingly use social media to meet their health information wants (HIW). Machine learning (ML) tools may help understand caregivers’ HIW as expressed via social media. This pilot study explored a collaborative, iterative process between domain experts and ML tools to identify ADRD caregivers’ HIW from social media data. The HIW-ADRD framework was adapted from an existing HIW framework. Through multiple rounds of iteration between the experts and the ML tools, the framework was expanded to include 11 types of health information. Each type included corresponding keywords developed through a hybrid approach that included keywords from both the theoretical constructs (top-down) and caregivers’ posts (bottom-up). These keywords were then used to enhance the ML tools’ ability to code 106 recent posts extracted from an ADRD social media group in March 2020. When compared with expert coding results, ML tools accurately predicted 56% of HIW. Further work is underway. |
format | Online Article Text |
id | pubmed-7742928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77429282020-12-21 Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach Xie, Bo Wang, Zhendong Zou, Ning Luo, Zhimeng Hilsabeck, Robin Aguirre, Alyssa Innov Aging Abstracts ADRD caregivers increasingly use social media to meet their health information wants (HIW). Machine learning (ML) tools may help understand caregivers’ HIW as expressed via social media. This pilot study explored a collaborative, iterative process between domain experts and ML tools to identify ADRD caregivers’ HIW from social media data. The HIW-ADRD framework was adapted from an existing HIW framework. Through multiple rounds of iteration between the experts and the ML tools, the framework was expanded to include 11 types of health information. Each type included corresponding keywords developed through a hybrid approach that included keywords from both the theoretical constructs (top-down) and caregivers’ posts (bottom-up). These keywords were then used to enhance the ML tools’ ability to code 106 recent posts extracted from an ADRD social media group in March 2020. When compared with expert coding results, ML tools accurately predicted 56% of HIW. Further work is underway. Oxford University Press 2020-12-16 /pmc/articles/PMC7742928/ http://dx.doi.org/10.1093/geroni/igaa057.2261 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstracts Xie, Bo Wang, Zhendong Zou, Ning Luo, Zhimeng Hilsabeck, Robin Aguirre, Alyssa Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach |
title | Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach |
title_full | Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach |
title_fullStr | Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach |
title_full_unstemmed | Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach |
title_short | Detecting ADRD Caregivers’ Information Wants in Social Media: A Machine Learning–Aided Approach |
title_sort | detecting adrd caregivers’ information wants in social media: a machine learning–aided approach |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7742928/ http://dx.doi.org/10.1093/geroni/igaa057.2261 |
work_keys_str_mv | AT xiebo detectingadrdcaregiversinformationwantsinsocialmediaamachinelearningaidedapproach AT wangzhendong detectingadrdcaregiversinformationwantsinsocialmediaamachinelearningaidedapproach AT zouning detectingadrdcaregiversinformationwantsinsocialmediaamachinelearningaidedapproach AT luozhimeng detectingadrdcaregiversinformationwantsinsocialmediaamachinelearningaidedapproach AT hilsabeckrobin detectingadrdcaregiversinformationwantsinsocialmediaamachinelearningaidedapproach AT aguirrealyssa detectingadrdcaregiversinformationwantsinsocialmediaamachinelearningaidedapproach |