The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China
With the rapid integration of artificial intelligence (AI) technologies in the field of education, public sentiment towards this development has gradually emerged as an important area of research. This study focuses on the sentiment analysis of online public opinions regarding the application of AI...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/6/3184 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849342897387732992 |
|---|---|
| author | Bowen Chen Jinqiao Zhou Hongfeng Zhang |
| author_facet | Bowen Chen Jinqiao Zhou Hongfeng Zhang |
| author_sort | Bowen Chen |
| collection | DOAJ |
| description | With the rapid integration of artificial intelligence (AI) technologies in the field of education, public sentiment towards this development has gradually emerged as an important area of research. This study focuses on the sentiment analysis of online public opinions regarding the application of AI in education. Python was used to scrape relevant online comments from various provinces in China. Using the SnowNLP algorithm, sentiments were classified into three categories: positive, neutral, and negative. The study primarily analyzes the spatial distribution characteristics of positive and negative sentiments, with a visualization of the results through Geographic Information Systems (GIS). Additionally, Moran’s I and Getis-Ord Gi* are introduced to detect the spatial autocorrelation of sentiment attitudes. Furthermore, by constructing a multivariable geographical detector model and MGWR, the study explores the impact of factors such as the development of the digital economy, the construction of smart cities, local government policy attention, the digital literacy of local residents, and the level of education infrastructure on the distribution of sentiment attitudes. This research will reveal the regional disparities in AI and education-related online public sentiment and its driving mechanisms, providing data support and empirical references for optimizing the application of AI in education. |
| format | Article |
| id | doaj-art-27fb9f08930849f7b41af2ceb83ba06a |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-27fb9f08930849f7b41af2ceb83ba06a2025-08-20T03:43:14ZengMDPI AGApplied Sciences2076-34172025-03-01156318410.3390/app15063184The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in ChinaBowen Chen0Jinqiao Zhou1Hongfeng Zhang2Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, ChinaFaculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, ChinaFaculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, ChinaWith the rapid integration of artificial intelligence (AI) technologies in the field of education, public sentiment towards this development has gradually emerged as an important area of research. This study focuses on the sentiment analysis of online public opinions regarding the application of AI in education. Python was used to scrape relevant online comments from various provinces in China. Using the SnowNLP algorithm, sentiments were classified into three categories: positive, neutral, and negative. The study primarily analyzes the spatial distribution characteristics of positive and negative sentiments, with a visualization of the results through Geographic Information Systems (GIS). Additionally, Moran’s I and Getis-Ord Gi* are introduced to detect the spatial autocorrelation of sentiment attitudes. Furthermore, by constructing a multivariable geographical detector model and MGWR, the study explores the impact of factors such as the development of the digital economy, the construction of smart cities, local government policy attention, the digital literacy of local residents, and the level of education infrastructure on the distribution of sentiment attitudes. This research will reveal the regional disparities in AI and education-related online public sentiment and its driving mechanisms, providing data support and empirical references for optimizing the application of AI in education.https://www.mdpi.com/2076-3417/15/6/3184AI educationSnowNLP computingspatial distributionspatial autocorrelationemotion analysisMGWR |
| spellingShingle | Bowen Chen Jinqiao Zhou Hongfeng Zhang The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China Applied Sciences AI education SnowNLP computing spatial distribution spatial autocorrelation emotion analysis MGWR |
| title | The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China |
| title_full | The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China |
| title_fullStr | The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China |
| title_full_unstemmed | The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China |
| title_short | The Media Spatial Diffusion Effect and Distribution Characteristics of AI in Education: An Empirical Analysis of Public Sentiments Across Provincial Regions in China |
| title_sort | media spatial diffusion effect and distribution characteristics of ai in education an empirical analysis of public sentiments across provincial regions in china |
| topic | AI education SnowNLP computing spatial distribution spatial autocorrelation emotion analysis MGWR |
| url | https://www.mdpi.com/2076-3417/15/6/3184 |
| work_keys_str_mv | AT bowenchen themediaspatialdiffusioneffectanddistributioncharacteristicsofaiineducationanempiricalanalysisofpublicsentimentsacrossprovincialregionsinchina AT jinqiaozhou themediaspatialdiffusioneffectanddistributioncharacteristicsofaiineducationanempiricalanalysisofpublicsentimentsacrossprovincialregionsinchina AT hongfengzhang themediaspatialdiffusioneffectanddistributioncharacteristicsofaiineducationanempiricalanalysisofpublicsentimentsacrossprovincialregionsinchina AT bowenchen mediaspatialdiffusioneffectanddistributioncharacteristicsofaiineducationanempiricalanalysisofpublicsentimentsacrossprovincialregionsinchina AT jinqiaozhou mediaspatialdiffusioneffectanddistributioncharacteristicsofaiineducationanempiricalanalysisofpublicsentimentsacrossprovincialregionsinchina AT hongfengzhang mediaspatialdiffusioneffectanddistributioncharacteristicsofaiineducationanempiricalanalysisofpublicsentimentsacrossprovincialregionsinchina |