## 4 Discussion
### Factors Influencing of Sentiment Attitudes
#### 4.3.1 Discussion Based on the Geo-Detector  
The results of the Geo-Detector analysis reveal that urban development levels (such as per capita disposable income, urbanization rate, and population density) are core variables affecting public sentiment towards AI education. In regions with higher income and more advanced modernization, the public tends to exhibit higher levels of positive sentiment. This is closely related to their openness to new technological applications, their stronger ability to adapt to new changes, and their higher capacity to handle technological transformations. Technological innovation resources (such as the number of patents granted and the number of people employed in information services) also play an important role in shaping sentiment attitudes [20]. High sentiment-value regions are often accompanied by stronger community support, increased public interaction, and the sharing of experiences, which in turn creates a positive public opinion atmosphere. This attracts more users to participate in technology applications and develop positive experiences. Areas rich in technological innovation resources have a more timely and widespread understanding of AI technology, leading to a higher sensitivity and attention to the trends of new technology applications in the local public [43].  
It is important to note that informatization infrastructure (such as the number of internet users and educational funding) has a relatively weaker impact on sentiment attitudes. This result suggests that improving information infrastructure alone may not be sufficient to significantly alter the public's emotional orientation towards AI education. In contrast, the combined effects of economic development and technological innovation capacity play a more critical role. Additionally, government policies related to the digital economy have limited direct impact but may exert influence indirectly through economic development and technological progress.  
The differences in AI education sentiment attitudes between the eastern coastal and western regions result from the interplay of multiple factors. The eastern regions typically exhibit higher economic development levels, urbanization rates, informatization levels, and technological innovation capabilities, all of which contribute to a more positive recognition and acceptance of AI education. Higher levels of urban development mean stronger technology acceptance, a smaller digital divide, and greater convenience in accessing information and services. The public in these areas has better access to information about AI education, fostering a favorable social interaction atmosphere that facilitates acceptance of new technology. In contrast, the lower sentiment intensity in the western regions reflects insufficient public understanding and discussion of AI education. This lack of recognition and discussion likely stems from limited channels for information acquisition. In areas with lower urban development levels, public exposure to emerging technologies is minimal, and local media coverage of relevant topics is scarce, leading to a lack of discussion spaces. This lack of awareness is a key factor in the formation of a relatively low emotional expression state, rather than complete rejection of technology [44].