Journal of Geodesy and Geoinformation Science ›› 2022, Vol. 5 ›› Issue (2): 98-110.doi: 10.11947/j.JGGS.2022.0210

• Special Issue • Previous Articles     Next Articles

Spatial-temporal Analysis of Emotions in Society in News

An HUAI1,2(),Xueying ZHANG1,2(),Weicheng AI1,2,Tianyang CAO1,2   

  1. 1. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
    2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2021-12-10 Accepted:2022-05-05 Online:2022-06-20 Published:2022-07-22
  • Contact: Xueying ZHANG;
  • About author:An HUAI (1997—), male, master, mainly engaged in human and social geographic information science research. E-mail:
  • Supported by:
    National Natural Science Foundation of China(41971337)


Spatial-temporal analysis of emotions in society has become popular in many studies integrating geography with the humanities, and has shown its influence on social sensing and geo-computation for social sciences. Emotions in society are often volatile, irrational, and vulnerable to the social environment. A critical challenge is to analyze changes in long-term and large-scale emotions in society. In this paper, we propose exploiting this challenge by using spatial-temporal analysis. After extracting emotional, temporal, and spatial information, a spatial standardization approach based on adataset of administrative district changes addresses the problem of Chinese toponym changes. Finally, over 1.7 million news data from the People’s Daily from 1956 to 2014 were collected to explore the changes, spatial distribution, and driving factors of emotions in society using spatial-temporal analysis. The experimental results found that the spatial-temporal analysis of emotions in society in the news is consistent with the results of related sociological research.

Key words: spatial-temporal analysis; emotional change; newsdata; social sensing; long-term and large-scale emotion