Modeling Urbanization Perception: Emerging Topics on Hangzhou Future Sci-Tech City Development
The complexity of the study on urban systems poses the challenging problem of developing methodological approaches for analyzing and modeling social data, both from a quantitative and a qualitative perspective. This work presents the research conducted to explore the perception on the urban development of an high-tech zone which has been recently established in China, i.e. Hangzhou Future Sci-Tech City. We conducted field research and collected data to identify which topics, concepts and interpretative categories are embedded in the social discourses about urban development and to derive the network of relations typical of complex social systems. The results of these analyses suggest that the perception of the people interviewed is mostly of great appreciation for the economic development with some concerns on the negative effects of this development on the society and the environment.
KeywordsUrbanization Perception Structural Topic Models Network of relations
This work was supported by the EU-CHINA Research and Innovation Partnership, EuropeAid/135-587/DD/ACT/Multi EU Project: New pathways for sustainable urban development in China’s medium-sized cities (MEDIUM). This publication has received funding from the European Union under the External actions of the European Union - Grant Contract ICI+/2014/348-005. The contents of this publication are the sole responsibility of the authors and can in no way be taken to reflect the views of the European Union.
- 6.Dolfin, M., Leonida, L., Outada. N.: Modeling human behavior in economics and social science. Phys. Life Rev. (2017, in press)Google Scholar
- 10.Tvinnereim, E., Liu, X., Jamelske, E.M.: Public perceptions of air pollution and climate change: different manifestations, similar causes, and concerns. Clim. Change 140, 1–14 (2016)Google Scholar
- 13.Roberts, M.E., Stewart, B.M., Tingley, D., Airoldi, E.M.: The structural topic model and applied social science. In: Neural Information Processing Society (2013)Google Scholar
- 16.Roberts, M.E., Stewart, B.M., Tingley, D.: STM: R-package for structural topic models. R package version 1.2.2 (2013). http://www.structuraltopicmodel.com