Cargando…
Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study
BACKGROUND: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. OBJECTIVE: The...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823583/ https://www.ncbi.nlm.nih.gov/pubmed/36563032 http://dx.doi.org/10.2196/24938 |
_version_ | 1784866195643564032 |
---|---|
author | Lokala, Usha Lamy, Francois Daniulaityte, Raminta Gaur, Manas Gyrard, Amelie Thirunarayan, Krishnaprasad Kursuncu, Ugur Sheth, Amit |
author_facet | Lokala, Usha Lamy, Francois Daniulaityte, Raminta Gaur, Manas Gyrard, Amelie Thirunarayan, Krishnaprasad Kursuncu, Ugur Sheth, Amit |
author_sort | Lokala, Usha |
collection | PubMed |
description | BACKGROUND: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. OBJECTIVE: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web forum data Prescription Drug Abuse Online Surveillance; analyzing patterns and trends of cannabis product use in the context of evolving cannabis legalization policies in the United States through analysis of Twitter and web forum data (eDrugTrends); assessing trends in the availability of novel synthetic opioids through the analysis of cryptomarket data (eDarkTrends); and analyzing COVID-19 pandemic trends in social media data related to 13 states in the United States as per Mental Health America reports. METHODS: The domain and scope of the DAO were defined using competency questions from popular ontology methodology (101 ontology development). The 101 method includes determining the domain and scope of ontology, reusing existing knowledge, enumerating important terms in ontology, defining the classes, their properties and creating instances of the classes. The quality of the ontology was evaluated using a set of tools and best practices recognized by the semantic web community and the artificial intelligence community that engage in natural language processing. RESULTS: The current version of the DAO comprises 315 classes, 31 relationships, and 814 instances among the classes. The ontology is flexible and can easily accommodate new concepts. The integration of the ontology with machine learning algorithms dramatically decreased the false alarm rate by adding external knowledge to the machine learning process. The ontology is recurrently updated to capture evolving concepts in different contexts and applied to analyze data related to social media and dark web marketplaces. CONCLUSIONS: The DAO provides a powerful framework and a useful resource that can be expanded and adapted to a wide range of substance use and mental health domains to help advance big data analytics of web-based data for substance use epidemiology research. |
format | Online Article Text |
id | pubmed-9823583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-98235832023-01-08 Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study Lokala, Usha Lamy, Francois Daniulaityte, Raminta Gaur, Manas Gyrard, Amelie Thirunarayan, Krishnaprasad Kursuncu, Ugur Sheth, Amit JMIR Public Health Surveill Original Paper BACKGROUND: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. OBJECTIVE: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web forum data Prescription Drug Abuse Online Surveillance; analyzing patterns and trends of cannabis product use in the context of evolving cannabis legalization policies in the United States through analysis of Twitter and web forum data (eDrugTrends); assessing trends in the availability of novel synthetic opioids through the analysis of cryptomarket data (eDarkTrends); and analyzing COVID-19 pandemic trends in social media data related to 13 states in the United States as per Mental Health America reports. METHODS: The domain and scope of the DAO were defined using competency questions from popular ontology methodology (101 ontology development). The 101 method includes determining the domain and scope of ontology, reusing existing knowledge, enumerating important terms in ontology, defining the classes, their properties and creating instances of the classes. The quality of the ontology was evaluated using a set of tools and best practices recognized by the semantic web community and the artificial intelligence community that engage in natural language processing. RESULTS: The current version of the DAO comprises 315 classes, 31 relationships, and 814 instances among the classes. The ontology is flexible and can easily accommodate new concepts. The integration of the ontology with machine learning algorithms dramatically decreased the false alarm rate by adding external knowledge to the machine learning process. The ontology is recurrently updated to capture evolving concepts in different contexts and applied to analyze data related to social media and dark web marketplaces. CONCLUSIONS: The DAO provides a powerful framework and a useful resource that can be expanded and adapted to a wide range of substance use and mental health domains to help advance big data analytics of web-based data for substance use epidemiology research. JMIR Publications 2022-12-23 /pmc/articles/PMC9823583/ /pubmed/36563032 http://dx.doi.org/10.2196/24938 Text en ©Usha Lokala, Francois Lamy, Raminta Daniulaityte, Manas Gaur, Amelie Gyrard, Krishnaprasad Thirunarayan, Ugur Kursuncu, Amit Sheth. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 23.12.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Lokala, Usha Lamy, Francois Daniulaityte, Raminta Gaur, Manas Gyrard, Amelie Thirunarayan, Krishnaprasad Kursuncu, Ugur Sheth, Amit Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study |
title | Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study |
title_full | Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study |
title_fullStr | Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study |
title_full_unstemmed | Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study |
title_short | Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study |
title_sort | drug abuse ontology to harness web-based data for substance use epidemiology research: ontology development study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823583/ https://www.ncbi.nlm.nih.gov/pubmed/36563032 http://dx.doi.org/10.2196/24938 |
work_keys_str_mv | AT lokalausha drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT lamyfrancois drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT daniulaityteraminta drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT gaurmanas drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT gyrardamelie drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT thirunarayankrishnaprasad drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT kursuncuugur drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy AT shethamit drugabuseontologytoharnesswebbaseddataforsubstanceuseepidemiologyresearchontologydevelopmentstudy |