Using text analytics to apprehend urban sustainability development

Picheng Lee, Gary Kleinman, Chu hua Kuei

Research output: Contribution to journalArticle

Abstract

This research aims to specify critical urban sustainability issues by mining unstructured text data derived from the C40 city datasets of the Carbon Disclosure Project. The current study identifies underlying topical issues exhibited by text corpora, enables creation of smarter data visualizations, and forms useful profiles. Four underlying topical areas are examined: economic opportunities, climate risks, incentives to reduce greenhouse gas emissions, and emissions reduction activities. For each area, we built text data visualization profiles. Developing these text data visualization profiles enables greater attention to be paid to the list of topical issues shown in the profiles. Given the number of discovered topic issues, we generate an urban sustainability activity index and use it to identify which cities were detailing their actions toward becoming more sustainable cities. The city officials and municipal planners of either C40 or non-C40 cities worldwide can benchmark this study and put the process of text data visualization at the center of their process of generating citywide sustainable development.

Original languageEnglish
JournalSustainable Development
DOIs
StateAccepted/In press - 1 Jan 2020

Keywords

  • Carbon Disclosure Project
  • data visualization
  • sustainable development
  • text analytics
  • urban sustainability

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