Urban Narrative: Computational Linguistic Interpretation of Large Format Public Participation for Urban Infrastructure

Mark Dyer, Min-Hsien Weng, Shaoqun Wu, Tomas García Ferrari and Rachel Dyer
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Mark Dyer: School of Engineering, Hamilton University of Waikato, New Zealand
Min-Hsien Weng: School of Engineering, Hamilton University of Waikato, New Zealand
Shaoqun Wu: School of Engineering, Hamilton University of Waikato, New Zealand
Tomas García Ferrari: School of Engineering, Hamilton University of Waikato, New Zealand
Rachel Dyer: School of Engineering, Hamilton University of Waikato, New Zealand

Urban Planning, 2020, vol. 5, issue 4, 20-32

Abstract: Urban Narrative works at the interface between public participation and participatory design to support collaboration processes for urban planning and design. It applies computational linguistics to interpret large format public consultation by identifying shared interests and desired qualities for urban infrastructure services and utilities. As a proof of concept, data was used from the Christchurch public engagement initiative called ‘Share an Idea,’ where public thoughts, ideas, and opinions were expressed about the future redevelopment of Christchurch after the 2011 earthquakes. The data set was analysed to identify shared interests and desired connections between institutional, communal, or personal infrastructures with the physical urban infrastructures in terms of buildings, public places, and utilities. The data has been visualised using chord charts from the D3 JavaScript open source library to illustrate the existence of connections between soft and hard urban infrastructures along with individual contributions or stories. Lastly, the analysis was used to create an infographic design brief that compares and contrasts qualitative information from public consultation with quantitative municipal statistical data on well-being.

Keywords: city; computational linguistics; infrastructure; narratives; public participation; urban narrative (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:cog:urbpla:v5:y:2020:i:4:p:20-32

DOI: 10.17645/up.v5i4.3208

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