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Understanding peace through the world news
Peace is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and peacekeepers. During the last years, novel digital data streams have drastically changed the research in this field. The current s...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777429/ https://www.ncbi.nlm.nih.gov/pubmed/35079561 http://dx.doi.org/10.1140/epjds/s13688-022-00315-z |
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author | Voukelatou, Vasiliki Miliou, Ioanna Giannotti, Fosca Pappalardo, Luca |
author_facet | Voukelatou, Vasiliki Miliou, Ioanna Giannotti, Fosca Pappalardo, Luca |
author_sort | Voukelatou, Vasiliki |
collection | PubMed |
description | Peace is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and peacekeepers. During the last years, novel digital data streams have drastically changed the research in this field. The current study exploits information extracted from a new digital database called Global Data on Events, Location, and Tone (GDELT) to capture peace through the Global Peace Index (GPI). Applying predictive machine learning models, we demonstrate that news media attention from GDELT can be used as a proxy for measuring GPI at a monthly level. Additionally, we use explainable AI techniques to obtain the most important variables that drive the predictions. This analysis highlights each country’s profile and provides explanations for the predictions, and particularly for the errors and the events that drive these errors. We believe that digital data exploited by researchers, policymakers, and peacekeepers, with data science tools as powerful as machine learning, could contribute to maximizing the societal benefits and minimizing the risks to peace. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1140/epjds/s13688-022-00315-z. |
format | Online Article Text |
id | pubmed-8777429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-87774292022-01-21 Understanding peace through the world news Voukelatou, Vasiliki Miliou, Ioanna Giannotti, Fosca Pappalardo, Luca EPJ Data Sci Regular Article Peace is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and peacekeepers. During the last years, novel digital data streams have drastically changed the research in this field. The current study exploits information extracted from a new digital database called Global Data on Events, Location, and Tone (GDELT) to capture peace through the Global Peace Index (GPI). Applying predictive machine learning models, we demonstrate that news media attention from GDELT can be used as a proxy for measuring GPI at a monthly level. Additionally, we use explainable AI techniques to obtain the most important variables that drive the predictions. This analysis highlights each country’s profile and provides explanations for the predictions, and particularly for the errors and the events that drive these errors. We believe that digital data exploited by researchers, policymakers, and peacekeepers, with data science tools as powerful as machine learning, could contribute to maximizing the societal benefits and minimizing the risks to peace. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1140/epjds/s13688-022-00315-z. Springer Berlin Heidelberg 2022-01-21 2022 /pmc/articles/PMC8777429/ /pubmed/35079561 http://dx.doi.org/10.1140/epjds/s13688-022-00315-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Regular Article Voukelatou, Vasiliki Miliou, Ioanna Giannotti, Fosca Pappalardo, Luca Understanding peace through the world news |
title | Understanding peace through the world news |
title_full | Understanding peace through the world news |
title_fullStr | Understanding peace through the world news |
title_full_unstemmed | Understanding peace through the world news |
title_short | Understanding peace through the world news |
title_sort | understanding peace through the world news |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777429/ https://www.ncbi.nlm.nih.gov/pubmed/35079561 http://dx.doi.org/10.1140/epjds/s13688-022-00315-z |
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