@article{e39f3857e80a431d80c18ad423650747,
title = "Extracting human emotions at different places based on facial expressions and spatial clustering analysis",
abstract = "The emergence of big data enables us to evaluate the various human emotions at places from a statistical perspective by applying affective computing. In this study a novel framework for extracting human emotions from large-scale georeferenced photos at different places is proposed. After the construction of places based on spatial clustering of user-generated footprints collected from social media websites, online cognitive services are utilized to extract human emotions from facial expressions using state-of-the-art computer vision techniques. Two happiness metrics are defined for measuring the human emotions at different places. To validate the feasibility of the framework, we take 80 tourist attractions around the world as an example and a happiness ranking list of places is generated based on human emotions calculated over 2 million faces detected from greater than 6 million photos. Different kinds of geographical contexts are taken into consideration to find out the relationship between human emotions and environmental factors. Results show that much of the emotional variation at different places can be explained by a few factors such as openness. The research offers insights into integrating human emotions to enrich the understanding of sense of place in geography and in place-based GIS.",
author = "Yuhao Kang and Qingyuan Jia and Song Gao and Xiaohuan Zeng and Yueyao Wang and Stephan Angsuesser and Yu Liu and Xinyue Ye and Teng Fei",
note = "Funding Information: The authors would like to thank Wanjuan Bie, Shan Lu, and Dan{\textquoteright}nan Shen at Wuhan University, for their contributions on figures. We thank Timothy Prestby at UW-Madison for his help with language edits of earlier versions of this article. We also thank Jialin Wang, Zimo Zhang, Wenyuan Kong and Zijun Xu in the Place & Emotion Group, Urban Playground Lab, Wuhan University, for helpful discussions. The funding support for this research is provided by the Office of Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison with funding from the Wisconsin Alumni Research Foundation, and the Fund for National College Students Innovations Special Project of China (Grant No. 201810486033), Dr. Yu Liu is partially supported by the National Natural Science Foundation of China (41625003). Funding Information: The authors would like to thank Wanjuan Bie, Shan Lu, and Dan{\textquoteright}nan Shen at Wuhan University, for their contribu‐ tions on figures. We thank Timothy Prestby at UW‐Madison for his help with language edits of earlier versions of this article. We also thank Jialin Wang, Zimo Zhang, Wenyuan Kong and Zijun Xu in the Place & Emotion Group, Urban Playground Lab, Wuhan University, for helpful discussions. The funding support for this research is provided by the Office of Vice Chancellor for Research and Graduate Education at the University of Wisconsin‐ Madison with funding from the Wisconsin Alumni Research Foundation, and the Fund for National College Students Innovations Special Project of China (Grant No. 201810486033), Dr. Yu Liu is partially supported by the National Natural Science Foundation of China (41625003). Publisher Copyright: {\textcopyright} 2019 John Wiley & Sons Ltd",
year = "2019",
month = jun,
doi = "10.1111/tgis.12552",
language = "English (US)",
volume = "23",
pages = "450--480",
journal = "Transactions in GIS",
issn = "1361-1682",
publisher = "Wiley-Blackwell",
number = "3",
}