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Conference Paper/Proceeding/Abstract 262 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

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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...

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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
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first_indexed 2023-09-12T15:45:30Z
last_indexed 2023-09-12T15:45:30Z
id cronfa64514
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spelling v2 64514 2023-09-12 Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health 43e704698d5dbbac3734b7cd0fef60aa 0000-0003-1373-6634 Frederic Boy Frederic Boy true false 2023-09-12 BBU 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. Conference Paper/Proceeding/Abstract IEEE International Symposium on Technology and Society (ISTAS) 224 232 IEEE 979-8-3503-2486-0/23/$31.00 Personal well-being, Google Trends™, COVID-19, forecasting, Search-Listening, Social-Listening, Epidemic intelligence 13 9 2023 2023-09-13 979-8-3503-2486-0/23/$31.00 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2023-10-24T09:06:35.1264580 2023-09-12T16:37:17.4505864 Faculty of Humanities and Social Sciences School of Management - Business Management Frederic Boy 0000-0003-1373-6634 1
title Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
spellingShingle Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
Frederic Boy
title_short Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
title_full Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
title_fullStr Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
title_full_unstemmed Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
title_sort Google Trends Dynamics for the Guidance of Open-Source Intelligence: Augmentation of Social-Media and Survey Surveillance of Population Mental Health
author_id_str_mv 43e704698d5dbbac3734b7cd0fef60aa
author_id_fullname_str_mv 43e704698d5dbbac3734b7cd0fef60aa_***_Frederic Boy
author Frederic Boy
author2 Frederic Boy
format Conference Paper/Proceeding/Abstract
container_title IEEE International Symposium on Technology and Society (ISTAS)
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publishDate 2023
institution Swansea University
isbn 979-8-3503-2486-0/23/$31.00
doi_str_mv 979-8-3503-2486-0/23/$31.00
publisher IEEE
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
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description 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.
published_date 2023-09-13T09:06:36Z
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score 11.012678

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