No Cover Image

Conference Paper/Proceeding/Abstract 238 views

Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health

Frederic Boy Orcid Logo

IEEE International Symposium on Technology and Society (ISTAS), Pages: 224 - 232

Swansea University Author: Frederic Boy Orcid Logo

Full text not available from this repository: check for access using links below.

DOI (Published version): 979-8-3503-2486-0/23/$31.00

Abstract

The unfolding of the COVID-19 outbreak was an unprecedented and unanticipated opportunity to understand how a sudden global shock modulates people’s online searches when seeking information about their emotional well-being. It has also illustrated how public health surveillance systems were essentia...

Full description

Published in: IEEE International Symposium on Technology and Society (ISTAS)
ISBN: 979-8-3503-2486-0/23/$31.00
Published: IEEE 2023
URI: https://cronfa.swan.ac.uk/Record/cronfa64514
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: The unfolding of the COVID-19 outbreak was an unprecedented and unanticipated opportunity to understand how a sudden global shock modulates people’s online searches when seeking information about their emotional well-being. It has also illustrated how public health surveillance systems were essential for tracking diseases’ spatial and temporal dynamics and shaping rapid public policy changes. The present paper validates a data mining and processing framework which examines how digital epidemiology and machine learning reveal trends in human mental health and psychological distress expression variability. We present results obtained in two research exploring the relationship between Google Trends time-series in the digital surveillance of search engines during the pandemic and a selection of social media feeds and official UK well-being surveys. The generated body of evidence shows how data science can provide robust, finely grained, and replicable evidence on mental health measures at the population level. In the future, the digital surveillance analytics validated here can be rapidly deployed for crisis management and allow early detection of distress signals to better manage communication and policy action at population level.
Keywords: Personal well-being, Google Trends™, COVID-19, forecasting, Search-Listening, Social-Listening, Epidemic intelligence
College: Faculty of Humanities and Social Sciences
Start Page: 224
End Page: 232