Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis
This paper delves into the economic policies of China during the pandemic and investigates the relationships between policy-issuing institutions. Firstly, we conduct keyword extraction and statistical analysis based on policy texts to understand policy contents and distribution. Then, we calculate t...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Connection Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/09540091.2023.2298073 |
| _version_ | 1797224636646162432 |
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| author | Miao Yu Xing Wan Tianyou Zhu Yuyue Wang Mengdi Xu Zhenzhen Wu Xinyu Li |
| author_facet | Miao Yu Xing Wan Tianyou Zhu Yuyue Wang Mengdi Xu Zhenzhen Wu Xinyu Li |
| author_sort | Miao Yu |
| collection | DOAJ |
| description | This paper delves into the economic policies of China during the pandemic and investigates the relationships between policy-issuing institutions. Firstly, we conduct keyword extraction and statistical analysis based on policy texts to understand policy contents and distribution. Then, we calculate the co-occurrence matrix of policy keywords and publishers from social networks and visualise the relationships with UCINET6 and Gephi software. Through a combination of semantic analysis and social network analysis, we examine the content of relevant economic policies, laws, regulations, and the relationships between their publishers. Our findings reveal three stages of China’s economic policies during the crisis, i.e. the shock, stable, and boost periods, which align with the crisis’s impact on China’s economy. Initial policies supported small-sized enterprises (SMEs), followed by a focus on industries like tourism. During the boost phase, policies underscored various support measures, including tax and fee reductions. We also identified a “local agglomeration” characteristic among policy-issuing entities, suggesting potential improvements in cooperation, especially at the provincial level. Our findings provide valuable insights for future policy design in response to public security events. |
| first_indexed | 2024-04-24T13:56:16Z |
| format | Article |
| id | doaj.art-e1b256ccaf874dfda8470f39f17d9749 |
| institution | Directory Open Access Journal |
| issn | 0954-0091 1360-0494 |
| language | English |
| last_indexed | 2024-04-24T13:56:16Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Connection Science |
| spelling | doaj.art-e1b256ccaf874dfda8470f39f17d97492024-04-03T17:51:46ZengTaylor & Francis GroupConnection Science0954-00911360-04942024-12-0136110.1080/09540091.2023.2298073Economic policies assessment and judgement during the pandemic with semantic and social network joint analysisMiao Yu0Xing Wan1Tianyou Zhu2Yuyue Wang3Mengdi Xu4Zhenzhen Wu5Xinyu Li6Business School of China University of Political Science and Law, Beijing, People’s Republic of ChinaBusiness School of China University of Political Science and Law, Beijing, People’s Republic of ChinaBusiness School of China University of Political Science and Law, Beijing, People’s Republic of ChinaBusiness School of China University of Political Science and Law, Beijing, People’s Republic of ChinaBusiness School of China University of Political Science and Law, Beijing, People’s Republic of ChinaBusiness School of China University of Political Science and Law, Beijing, People’s Republic of ChinaBusiness School of China University of Political Science and Law, Beijing, People’s Republic of ChinaThis paper delves into the economic policies of China during the pandemic and investigates the relationships between policy-issuing institutions. Firstly, we conduct keyword extraction and statistical analysis based on policy texts to understand policy contents and distribution. Then, we calculate the co-occurrence matrix of policy keywords and publishers from social networks and visualise the relationships with UCINET6 and Gephi software. Through a combination of semantic analysis and social network analysis, we examine the content of relevant economic policies, laws, regulations, and the relationships between their publishers. Our findings reveal three stages of China’s economic policies during the crisis, i.e. the shock, stable, and boost periods, which align with the crisis’s impact on China’s economy. Initial policies supported small-sized enterprises (SMEs), followed by a focus on industries like tourism. During the boost phase, policies underscored various support measures, including tax and fee reductions. We also identified a “local agglomeration” characteristic among policy-issuing entities, suggesting potential improvements in cooperation, especially at the provincial level. Our findings provide valuable insights for future policy design in response to public security events.https://www.tandfonline.com/doi/10.1080/09540091.2023.2298073Semantic analysissocial network analysiseconomic policy contenteconomic security |
| spellingShingle | Miao Yu Xing Wan Tianyou Zhu Yuyue Wang Mengdi Xu Zhenzhen Wu Xinyu Li Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis Connection Science Semantic analysis social network analysis economic policy content economic security |
| title | Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis |
| title_full | Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis |
| title_fullStr | Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis |
| title_full_unstemmed | Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis |
| title_short | Economic policies assessment and judgement during the pandemic with semantic and social network joint analysis |
| title_sort | economic policies assessment and judgement during the pandemic with semantic and social network joint analysis |
| topic | Semantic analysis social network analysis economic policy content economic security |
| url | https://www.tandfonline.com/doi/10.1080/09540091.2023.2298073 |
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