Yue Ma

Ms. Yue Ma


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
Open access
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YMYue Ma
Yue Ma
CLChanglong Ling
Changlong Ling
JWJing Wu
Jing Wu
The benefits of the natural environment in urban space have been explored in numerous studies. However, only a few statistics and studies have been conducted on the correlation between emotion and urban waterfront space, especially considering gender differences. Taking Wuhan city as an example, this study puts forward a new approach and perspective. Text emotion analysis is combined with the spatial analysis technique based on big data of social media. Based on the emotions of the public of different genders in urban space, suggestions are provided for urban planning and development from the perspective of POI (Point of Interest). The main steps are: (1) Analyzing the emotional score of Weibo texts published by citizens in the waterfront area of 21 lakes in Wuhan City; (2) exploring the public emotion characteristics of different genders in the urban waterfront; (3) classifying the waterfront according to the emotional response (score) of the public of different genders; (4) exploring the relationship between different POI types and waterfront types and proposing planning suggestions. The results of this study provide evidence for gender differences and spatial distribution of public emotions in the Wuhan waterfront area. It can help decision-makers to judge the prior protection and development direction of waterfront space, thus demonstrating the feasibility of this approach.

Verified
Journal Article
Open access
PDF file
JWJing Wu
Jing Wu
JLJingwen Li
Jingwen Li
YMYue Ma
Yue Ma
The geographical location and check-in frequency of social platform users indicate their personal preferences and intentions for space. On the basis of social media data and gender differences, this study analyzes Weibo users’ preferences and the reasons behind these preferences for the waterfronts of the 21 major lakes within Wuhan’s Third Ring Road, in accordance with users’ check-in behaviors. According to the distribution characteristics of the waterfronts’ points of interest, this study explores the preferences of male and female users for waterfronts and reveals, through the check-in behaviors of Weibo users, the gender differences in the preference and willingness of these users to choose urban waterfronts. Results show that men and women check in significantly more frequently on weekends than on weekdays. Women are more likely than men to check in at waterfronts. Significant differences in time and space exist between male and female users’ preferences for different lakes.