Objective The objective of current urban construction in China is to enhance and optimize the quality of the built environment in order to improve the people’s sense of well-being and sense of gain, which has become a top priority for urban development. As the public is the principal constituent of the built environment, it is of utmost importance to have a clear comprehension of the public’s sentimental demand for the built environment in order to achieve high-quality urban development and promote the public’s sense of well-being. This research aims to, by gaining a deep understanding of the public’s sentimental needs, steers urban planning and construction towards creating a more habitable environment that better satisfies the people’s expectations.
Methods The development of emotion research is first examined, including changes in emotion research theories and research methods. By virtue of the CiteSpace bibliometric analysis software, this research illustrates and scrutinizes the contemporary research development and salient aspects of public sentiment experience and built environment. By examining an extensive corpus of literature, the research extracts and elucidates the attributes of sentiment research from the three dimensions of data, content and method. To grasp the shifting dynamics of public sentiments more effectively, the research proposes a series of processes applicable to urban sentiment surveillance and discernment, thereby capturing the public’s sentiments in a more inclusive and systematic manner.
Results Sentiment classification theories can be broadly categorized into two main groups: basic emotion theory and emotion dimension theory. The theory of emotion, stemming from the accumulation of emotions, has evolved through the integration of landscape aesthetics, environmental psychology, and other significant theories in landscape gardening. Furthermore, in the context of multidisciplinary integration, the reciprocal exchange of research methods and theories across different disciplines has contributed to a more comprehensive perspective in the field of emotion research. With the advent of the 21st century, urbanization has ushered in both convenience and environmental degradation. It is crucial to recognize the dual impact of urbanization – the positive aspects of convenience and the negative consequences of environmental degradation. As cities evolve, the emphasis on creating sustainable and ecologically conscious urban spaces has become paramount. The shift towards garden cities and eco-friendly urban development reflects a collective recognition of the importance of preserving the environment amid rapid urban expansion. Despite these positive strides, there remains a notable gap in the design approach adopted for urban built environments. The prevailing focus on form and functionality, while essential, tends to sideline the emotional and psychological well-being of the urban residents. Furthermore, the spiritual connotations that an environment should embody are often neglected in the urban design discourse. The profound impact of surroundings on the human spirit and well-being is a crucial aspect that needs to be integrated into the design philosophy. Spaces should evoke a sense of belonging, cultural identity, and emotional resonance, thus contributing to a holistic urban experience. In light of these considerations, the call for emotional design becomes increasingly urgent. The research finds that the sources of data for sentiment research are primarily text-based, with relatively few direct analyses of image, speech or other forms of data. Furthermore, the research indicates that the current research mainly focuses on factors influencing positive sentiments, while paying less attention to negative sentiments. In terms of methodology, emotion recognition is a multimodal process, but there are significant variations in the quality and quantity of information available from different sources.
Conclusion The current research data on public sentiment research in urban built environment is characterized by a multitude of sources and types, however, the predominant data form is text data, and the direct analysis of such data forms as image and speech is relatively lacking. In the future, Convolutional Neural Network (CNN) models can be employed to process information found on social media platforms, such as comments and photos, and delve into the hidden meanings of pictures, such as irony, humor, metaphor and exaggeration. Sentiment classification can be enhanced through machine learning, and the attention mechanism can be introduced to extract useful information in sentiment analysis, thus adding credibility to subsequent built environment evaluations. The classification of the influences of the research on built environment sentiment on various population groups and spatial elements in cities is yet to be improved and comprehensively organized. To achieve sustainable development and enhance people’s sense of well-being, it is important for researchers to focus on the relationship between positive sentiments and the built environment at multiple scales, and understand the sentiment influencing mechanisms and paths of various spatial structures, landscape elements, and design elements in future city planning. The application of the research on built environment sentiment is mainly limited by the content and type of research, with varying quality and quantity of information across different scales. It is suggested to utilize the synergy between multiple data forms, such as incorporating digital technology-assisted measurement methods to strengthen the practical application of virtual reality technology. This will provide richer methodological and technological support for the research on built environment evaluation, improving the reliability, validity, and generalizability of research findings. These recommendations will be beneficial for expanding the direction of landscape architecture research and promoting design innovation.