Spatiotemporal analysis and forecasting of public attention to China’s five major religions
Abstract In the digital era, leveraging search engine data to gain insights into public interests and attitudes towards religion has become increasingly important. To examine the spatiotemporal evolution and develop a forecasting model of public attention to China’s five major religions (Buddhism, T...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-15396-9 |
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| author | Xianhang Xu Mohd Anuar Arshad Hong Liu Mengjiao Zhao Jiejing Yang Shuxia Cao Guoyu Luo Ming Chen Qianqian Chen |
| author_facet | Xianhang Xu Mohd Anuar Arshad Hong Liu Mengjiao Zhao Jiejing Yang Shuxia Cao Guoyu Luo Ming Chen Qianqian Chen |
| author_sort | Xianhang Xu |
| collection | DOAJ |
| description | Abstract In the digital era, leveraging search engine data to gain insights into public interests and attitudes towards religion has become increasingly important. To examine the spatiotemporal evolution and develop a forecasting model of public attention to China’s five major religions (Buddhism, Taoism, Catholicism, Christianity and Islam), this study introduces geographic information system technology, forecasting technology and spatiotemporal analysis methods into religious research, using Baidu Index data from 2020 to 2024. The results show that most religions exhibit stable annual public attention, although significant changes occur during specific seasons, festivals or events. Spatial variation in public attention is moderate, with a relatively balanced regional distribution. However, a distinct east–west clustering pattern is evident, reflecting spatial aggregation. The SARIMA-based forecasting model effectively captures temporal dynamics and demonstrates strong forecasting performance. Findings reveal the spatiotemporal distribution patterns of religious public attention and highlight the practical value of the forecasting model, thereby emphasising the importance of considering spatial factors and forecasting models when addressing the dissemination of religion in the digital age. This study provides new methods and perspectives for religious research, promoting an interdisciplinary synthesis of religious studies, sociology and geography. It offers new insights into global religious studies, religious communication strategies and cultural exchange. Furthermore, it contributes to advancing cross-cultural and cross-regional religious research and offers valuable references for religious organisations and policymakers in managing religious affairs, adjusting policies and optimising communication strategies in a globalised context. |
| format | Article |
| id | doaj-art-5698fbdf9948467993a3375adb7b05ff |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5698fbdf9948467993a3375adb7b05ff2025-08-20T03:04:25ZengNature PortfolioScientific Reports2045-23222025-08-0115111910.1038/s41598-025-15396-9Spatiotemporal analysis and forecasting of public attention to China’s five major religionsXianhang Xu0Mohd Anuar Arshad1Hong Liu2Mengjiao Zhao3Jiejing Yang4Shuxia Cao5Guoyu Luo6Ming Chen7Qianqian Chen8School of Management, Chongqing Institute of EngineeringSchool of Management, Universiti Sains MalaysiaSchool of Economics and Management, Tianjin Tianshi CollegeSchool of Management, Universiti Sains MalaysiaSchool of Management, Universiti Sains MalaysiaSchool of Management, Universiti Sains MalaysiaSchool of Management, Universiti Sains MalaysiaSchool of Business, Changshu Institute of TechnologySchool of Management, Chongqing Institute of EngineeringAbstract In the digital era, leveraging search engine data to gain insights into public interests and attitudes towards religion has become increasingly important. To examine the spatiotemporal evolution and develop a forecasting model of public attention to China’s five major religions (Buddhism, Taoism, Catholicism, Christianity and Islam), this study introduces geographic information system technology, forecasting technology and spatiotemporal analysis methods into religious research, using Baidu Index data from 2020 to 2024. The results show that most religions exhibit stable annual public attention, although significant changes occur during specific seasons, festivals or events. Spatial variation in public attention is moderate, with a relatively balanced regional distribution. However, a distinct east–west clustering pattern is evident, reflecting spatial aggregation. The SARIMA-based forecasting model effectively captures temporal dynamics and demonstrates strong forecasting performance. Findings reveal the spatiotemporal distribution patterns of religious public attention and highlight the practical value of the forecasting model, thereby emphasising the importance of considering spatial factors and forecasting models when addressing the dissemination of religion in the digital age. This study provides new methods and perspectives for religious research, promoting an interdisciplinary synthesis of religious studies, sociology and geography. It offers new insights into global religious studies, religious communication strategies and cultural exchange. Furthermore, it contributes to advancing cross-cultural and cross-regional religious research and offers valuable references for religious organisations and policymakers in managing religious affairs, adjusting policies and optimising communication strategies in a globalised context.https://doi.org/10.1038/s41598-025-15396-9Public attentionReligionSpatiotemporal analysisGIS technologyForecasting |
| spellingShingle | Xianhang Xu Mohd Anuar Arshad Hong Liu Mengjiao Zhao Jiejing Yang Shuxia Cao Guoyu Luo Ming Chen Qianqian Chen Spatiotemporal analysis and forecasting of public attention to China’s five major religions Scientific Reports Public attention Religion Spatiotemporal analysis GIS technology Forecasting |
| title | Spatiotemporal analysis and forecasting of public attention to China’s five major religions |
| title_full | Spatiotemporal analysis and forecasting of public attention to China’s five major religions |
| title_fullStr | Spatiotemporal analysis and forecasting of public attention to China’s five major religions |
| title_full_unstemmed | Spatiotemporal analysis and forecasting of public attention to China’s five major religions |
| title_short | Spatiotemporal analysis and forecasting of public attention to China’s five major religions |
| title_sort | spatiotemporal analysis and forecasting of public attention to china s five major religions |
| topic | Public attention Religion Spatiotemporal analysis GIS technology Forecasting |
| url | https://doi.org/10.1038/s41598-025-15396-9 |
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