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Google Trends in Infodemiology and Infoveillance: Methodology Framework

Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest i...

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Detalles Bibliográficos
Autores principales: Mavragani, Amaryllis, Ochoa, Gabriela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660120/
https://www.ncbi.nlm.nih.gov/pubmed/31144671
http://dx.doi.org/10.2196/13439
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author Mavragani, Amaryllis
Ochoa, Gabriela
author_facet Mavragani, Amaryllis
Ochoa, Gabriela
author_sort Mavragani, Amaryllis
collection PubMed
description Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest in selected keywords and topics over time. Online search traffic data from Google have been shown to be useful in analyzing human behavior toward health topics and in predicting disease occurrence and outbreaks. Despite the large number of Google Trends studies during the last decade, the literature on the subject lacks a specific methodology framework. This article aims at providing an overview of the tool and data and at presenting the first methodology framework in using Google Trends in infodemiology and infoveillance, including the main factors that need to be taken into account for a strong methodology base. We provide a step-by-step guide for the methodology that needs to be followed when using Google Trends and the essential aspects required for valid results in this line of research. At first, an overview of the tool and the data are presented, followed by an analysis of the key methodological points for ensuring the validity of the results, which include selecting the appropriate keyword(s), region(s), period, and category. Overall, this article presents and analyzes the key points that need to be considered to achieve a strong methodological basis for using Google Trends data, which is crucial for ensuring the value and validity of the results, as the analysis of online queries is extensively integrated in health research in the big data era.
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spelling pubmed-66601202019-07-31 Google Trends in Infodemiology and Infoveillance: Methodology Framework Mavragani, Amaryllis Ochoa, Gabriela JMIR Public Health Surveill Tutorial Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest in selected keywords and topics over time. Online search traffic data from Google have been shown to be useful in analyzing human behavior toward health topics and in predicting disease occurrence and outbreaks. Despite the large number of Google Trends studies during the last decade, the literature on the subject lacks a specific methodology framework. This article aims at providing an overview of the tool and data and at presenting the first methodology framework in using Google Trends in infodemiology and infoveillance, including the main factors that need to be taken into account for a strong methodology base. We provide a step-by-step guide for the methodology that needs to be followed when using Google Trends and the essential aspects required for valid results in this line of research. At first, an overview of the tool and the data are presented, followed by an analysis of the key methodological points for ensuring the validity of the results, which include selecting the appropriate keyword(s), region(s), period, and category. Overall, this article presents and analyzes the key points that need to be considered to achieve a strong methodological basis for using Google Trends data, which is crucial for ensuring the value and validity of the results, as the analysis of online queries is extensively integrated in health research in the big data era. JMIR Publications 2019-05-29 /pmc/articles/PMC6660120/ /pubmed/31144671 http://dx.doi.org/10.2196/13439 Text en ©Amaryllis Mavragani, Gabriela Ochoa. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 29.05.2019. 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 http://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Tutorial
Mavragani, Amaryllis
Ochoa, Gabriela
Google Trends in Infodemiology and Infoveillance: Methodology Framework
title Google Trends in Infodemiology and Infoveillance: Methodology Framework
title_full Google Trends in Infodemiology and Infoveillance: Methodology Framework
title_fullStr Google Trends in Infodemiology and Infoveillance: Methodology Framework
title_full_unstemmed Google Trends in Infodemiology and Infoveillance: Methodology Framework
title_short Google Trends in Infodemiology and Infoveillance: Methodology Framework
title_sort google trends in infodemiology and infoveillance: methodology framework
topic Tutorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660120/
https://www.ncbi.nlm.nih.gov/pubmed/31144671
http://dx.doi.org/10.2196/13439
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