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费腾、硕士生黄颖菁的论文在International Journal of Geo-Information 上刊出
发布时间:2020-09-23 11:04:21     发布者:易真     浏览次数:

标题: Based Emotional Computing: A Review of Quantitative Approaches to Measure the Emotion Layer of Human–Environment Relationships

作者: Yingjing Huang ,Teng Fei ,Mei-Po Kwan ,Yuhao Kang ,Jun Li ,Yizhuo Li ,Xiang Li andMeng Bian

来源出版物: International Journal of Geo-Information : 9  :9 :551  DOI: 10.3390/ijgi9090551 -  出版时间: Sep 2020

摘要: In recent years, with the growing accessibility of abundant contextual emotion information, which is benefited by the numerous georeferenced user-generated content and the maturity of artificial intelligence (AI)-based emotional computing technics, the emotion layer of human–environment relationship is proposed for enriching traditional methods of various related disciplines such as urban planning. This paper proposes the geographic information system (GIS)-based emotional computing concept, which is a novel framework for applying GIS methods to collective human emotion. The methodology presented in this paper consists of three key steps: (1) collecting georeferenced data containing emotion and environment information such as social media and official sites, (2) detecting emotions using AI-based emotional computing technics such as natural language processing (NLP) and computer vision (CV), and (3) visualizing and analyzing the spatiotemporal patterns with GIS tools. This methodology is a great synergy of multidisciplinary cutting-edge techniques, such as GIScience, sociology, and computer science. Moreover, it can effectively and deeply explore the connection between people and their surroundings with the help of GIS methods. Generally, the framework provides a standard workflow to calculate and analyze the new information layer for researchers, in which a measured human-centric perspective onto the environment is possible.

地址:

[Yingjing Huang ,Teng Fei, Jun Li]School of Resource and Environmental Sciences, Wuhan University, Wuhan 430000, China

[Mei-Po Kwan]Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong, China;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong, China;Department of Human Geography and Spatial Planning, Utrecht University, 3584 CB Utrecht, The Netherlands

[Yuhao Kang]Geospatial Data Science Lab, Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA

[Xiang Li]Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450000, China

[Meng Bian]School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430000, China

通讯作者地址: Teng Fei, School of Resource and Environmental Sciences, Wuhan University, Wuhan 430000, China

电子邮件地址: feiteng@whu.edu.cn

影响因子:2.239


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