Abstract
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.
Highlights
The human–environment relationship has always been a key issue in geography in terms of the interaction between human society and its activities and geographical environment [1,2,3]
In this paper, we propose a new conceptual framework: geographic information system (GIS)-based emotional computing, for providing a new approach to measure the emotion layer of human–environment relationship
We propose a new conceptual framework: GIS-based emotional computing, for providing a new approach to measure the emotion layer of human–environment relationship
Summary
The human–environment relationship has always been a key issue in geography in terms of the interaction between human society and its activities and geographical environment [1,2,3]. We present a novel research framework, which equips collective emotion with geographic information system (GIS) methods to quantitatively measure the emotion layer of human–environment relationship, namely GIS-based emotional computing. The framework comprises three key steps: first, collecting environment and emotion related data in various context from data sources such as social network sites and official sites; second, exploring and cleaning data and extracting emotional information from georeferenced emotion related data based on its data structure; and third, conducting spatiotemporal analysis using GIS methods such as spatial interpolation and kernel density analysis in order to provide researchers with additional insights into the complex human–environment relationship.
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