A value of civic voices for smart city: A big data analysis of civic queries posed by Seoul citizens. (January 2021)

• Record Type: Journal Article
• Authors: Kim, Byungjun; Yoo, Minjoo; Park, Keon Chul; Lee, Kyeo Re; Kim, Jang Hyun
• Is Part Of: Cities. Volume 108(2021)
• Publication Date: 2021-01
• Subjects: Word2vec -- Dynamic topic model -- Civil complaints -- Automatic classification -- Smart city; City planning -- Periodicals; Urban policy -- Periodicals; 711.4
• DOI: 10.1016/j.cities.2020.102941
• Languages: English
• ISSNs: 0264-2751

Abstract

Abstract: Since urban problems are increasingly becoming complex and multifaceted due to the rapid urbanization, interest in the development of smart cities as an efficient solution to such problems is growing. The significance of smart cities lies in not having technology itself but using technology with a novel approach to solve urban problems, enhance the quality of life for urban residents, and optimize government performance. Such an approach includes scientifically processing civic query (including complaints, suggestions, and inquiry) data about a city and planning the city such that its policies reflect its residents' voices to ensure "throughput legitimacy." This study introduces a novel approach to analyze diverse informal civic query data for a city and plan the city in a way that its residents want. By analyzing 160, 000 civic queries accumulated over 10 years from 2006 to 2017 from the "Oasis of 10 Million Imagination, " which is a civic participation platform of Seoul, this study aims to contribute to the sustainable development of Seoul so that it can plan a citizen-centric and smart city that satisfies the demands of its residents. By applying Dynamic Topic Model, the authors intend to specify civic demands and forecast the demands of citizens. Highlights: This study introduces a novel approach to analyze diverse civic query data submitted online. Analyzed 160, 000 civic queries accumulated over 10 years from 2006 to 2017 from the online venue of Seoul city, South Korea. Machine learning/artificial intelligence (AI) would enhance the quality of responsive governance. Dynamic topic model and Word2vec combined for detecting civic complaints. City government should provide data-driven insights for its citizens.