Text Mining Based Exploration of Smart City Building Development

Zhikun Ding (), Zongjie Li and Ting Hu
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Zhikun Ding: Shenzhen University
Zongjie Li: Shenzhen University
Ting Hu: Shenzhen University

A chapter in Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 694-709 from Springer

Abstract: Abstract Driven by urban informationization and data science, smart city is becoming a hot topic for future urban development on a global scale. Buildings in the context of smart city will have a direct impact on future urban digital progress. Therefore, the study of building development driven by smart city is of great significance. However, the exponential growth in the volume of associated literature has become a challenge for the systematic analysis by researchers and policymakers. This paper applied the topic model research method based on text mining to analyze 538 academic papers related to smart city buildings between 2010 and 2018. The results of top words in terms of TF-IDF showed that “Energy” and “IoT (Internet of things)” are the two main themes of study. The topic model provided a further division and explanation of textual data. The results showed that the research on building development in smart city mainly focuses on building energy consumption, IoT in buildings, building informatization, government regulation, intelligent building design, smart home. At the same time, the proportion of research on building energy consumption, building informatization, and government regulation is increasing. This study can help researchers to establish knowledge framework of smart city building development and provide decision support for governments.

Keywords: Smart city; Building; Text mining; Topic model (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-3977-0_53

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DOI: 10.1007/978-981-15-3977-0_53

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