Analysis of the evolving factors of social media users' emotions and behaviors: a longitudinal study from China's COVID-19 opening policy period.

The outbreak of the COVID-19 pandemic has triggered citizen panic and social crises worldwide. The Chinese government was the first to implement strict prevention and control policies. However, in December 2022, the Chinese government suddenly changed its prevention and control policies and completely opened up. This led to a large-scale infection of the epidemic in a short period of time, which will cause unknown social impacts. This study collected 500+ epidemic-related hotspots and 200,000+ data from November 1, 2022, to March 1, 2023. Using a sentiment classification method based on pre-trained neural network models, we conducted inductive analysis and a summary of high-frequency words of various emotions. This study focuses on the inflection point of the emotional evolution of social media users and the evolution of "hot topic searches" events and emotional behavioral factors after the sudden open policy. Our research results show that, first of all, the positive emotions of social media users are divided into 4 inflection points and 5 time periods, and the negative emotions are divided into 3 inflection points and 4 time periods. Behavioral factors are different at each stage of each emotion. And the evolution patterns of positive emotions and negative emotions are also different. Secondly, the evolution of behavioral elements deserves more attention. Continue to pay attention: The treatment of diseases, the recovery of personal health, the promotion of festive atmosphere, and the reduction of publicity on the harm of "new crown sequelae and second infections" are the behavioral concerns that affect users' emotional changes. Finally, it is necessary to change the "hot topic searches" event by guiding the user's behavioral focus to control the inflection point of the user's emotion. This study helps governments and institutions understand the dynamic impact of epidemic policy changes on social media users, thereby promoting policy formulation and better coping with social crises.

An overview and trend analysis of research on the relationship between urban streets and residents' health in China pre- and post COVID-19 pandemic.

Introduction: After the outbreak of COVID-19, the international community has been faced with various problems it has brought to cities. A large number of research projects and corresponding management measures were launched globally, trying to reduce the impact of COVID-19 on society. Among them, exploring how to maintain the health of residents by managing and updating the design of urban streets is one of the important issues regarding urban sustainability in the post-epidemic era. Methods: This study uses bibliometric analysis techniques to obtain an overview of the knowledge structure of 898 Chinese urban streets and residents' health relationship studies from the China National Knowledge Infrastructure (CNKI) database for two periods (1999-2019 and 2020-2022). Five aspects were analyzed in terms of the keyword domain co-occurrence network, topic evolution path, emergent terms, hierarchical clustering, and confusion matrix. Results and discussion: The findings revealed that studies focused on six broad themes: community residents, health surveys, health education, COVID-19, healthy city, and public health. Based on these findings, the paper compares and discusses research priorities before and after the outbreak and highlights areas for further research and attention.

Research on Constructing a Healing Environment for the Street Spaces of a High-Density City: Using Street Spaces in Macao's Old City Area.

It is commonly recognized that street spaces in high-density cities are able to cause negative impacts in terms of residents' physical and mental health. This research intends to investigate and analyze how residents use street spaces in a high-density city in order to construct a healing environment for these street spaces. The research was conducted in Macao's old town by using spatial syntax methods to define the research areas, and implemented on-site observations that evaluated the age of the residents in the space and the conditions of their usage of the space. The study collected data through expert grading and employed the Analytic Hierarchy Process to calculate the weight of each indicator in order to attain accurate and objective research outcomes. The evaluation results indicate that the current Macao street spaces are poor healing environments. By analyzing the effective factors for constructing a healing environment in these street spaces, so that residents can get more space for healing when they use it, the paper aims to provide a model example for those who are involved with city governance, planning and design.