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Free trade as domestic, economic, and strategic issues: a big data analytics approach
This article examines the engagement of domestic actors in public conversation surrounding free trade negotiations with a focus on the framing of these negotiations as economic, strategic or domestic issues. To analyse this topic, this article utilises the use of Twitter as a barometer of public sen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104431/ https://www.ncbi.nlm.nih.gov/pubmed/37089901 http://dx.doi.org/10.1186/s40537-023-00722-7 |
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author | Karim, Moch Faisal Rahutomo, Reza Manuaba, Ida Bagus Kerthyayana Purwandari, Kartika Mursitama, Tirta Nugraha Pardamean, Bens |
author_facet | Karim, Moch Faisal Rahutomo, Reza Manuaba, Ida Bagus Kerthyayana Purwandari, Kartika Mursitama, Tirta Nugraha Pardamean, Bens |
author_sort | Karim, Moch Faisal |
collection | PubMed |
description | This article examines the engagement of domestic actors in public conversation surrounding free trade negotiations with a focus on the framing of these negotiations as economic, strategic or domestic issues. To analyse this topic, this article utilises the use of Twitter as a barometer of public sentiment toward the Regional Comprehensive Economic Partnership (RCEP). We employ topic classification and sentiment analysis to understand how RCEP is discussed in 345,015 tweets. Our findings show that the overall sentiment score towards RCEP is neutral. However, we find that when RCEP is discussed as a strategic issue, the sentiment is slightly more negative than when discussed as a domestic or economic issue. This article further suggests that discussion of RCEP is driven by the fear of China’s geopolitical ambitions, domestic protectionist agendas, and impact of RCEP on the domestic economy. This article contributes to the growing use of big data in understanding trade negotiations. Furthermore, it contributes to the study of free trade negotiation by examining how domestic political actors frame free trade negotiations. |
format | Online Article Text |
id | pubmed-10104431 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-101044312023-04-17 Free trade as domestic, economic, and strategic issues: a big data analytics approach Karim, Moch Faisal Rahutomo, Reza Manuaba, Ida Bagus Kerthyayana Purwandari, Kartika Mursitama, Tirta Nugraha Pardamean, Bens J Big Data Research This article examines the engagement of domestic actors in public conversation surrounding free trade negotiations with a focus on the framing of these negotiations as economic, strategic or domestic issues. To analyse this topic, this article utilises the use of Twitter as a barometer of public sentiment toward the Regional Comprehensive Economic Partnership (RCEP). We employ topic classification and sentiment analysis to understand how RCEP is discussed in 345,015 tweets. Our findings show that the overall sentiment score towards RCEP is neutral. However, we find that when RCEP is discussed as a strategic issue, the sentiment is slightly more negative than when discussed as a domestic or economic issue. This article further suggests that discussion of RCEP is driven by the fear of China’s geopolitical ambitions, domestic protectionist agendas, and impact of RCEP on the domestic economy. This article contributes to the growing use of big data in understanding trade negotiations. Furthermore, it contributes to the study of free trade negotiation by examining how domestic political actors frame free trade negotiations. Springer International Publishing 2023-04-14 2023 /pmc/articles/PMC10104431/ /pubmed/37089901 http://dx.doi.org/10.1186/s40537-023-00722-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 | Research Karim, Moch Faisal Rahutomo, Reza Manuaba, Ida Bagus Kerthyayana Purwandari, Kartika Mursitama, Tirta Nugraha Pardamean, Bens Free trade as domestic, economic, and strategic issues: a big data analytics approach |
title | Free trade as domestic, economic, and strategic issues: a big data analytics approach |
title_full | Free trade as domestic, economic, and strategic issues: a big data analytics approach |
title_fullStr | Free trade as domestic, economic, and strategic issues: a big data analytics approach |
title_full_unstemmed | Free trade as domestic, economic, and strategic issues: a big data analytics approach |
title_short | Free trade as domestic, economic, and strategic issues: a big data analytics approach |
title_sort | free trade as domestic, economic, and strategic issues: a big data analytics approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104431/ https://www.ncbi.nlm.nih.gov/pubmed/37089901 http://dx.doi.org/10.1186/s40537-023-00722-7 |
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