Image of a City through Big Data Analytics: Colombo from the Lens of Geo-Coded Social Media Data

Sandulika Abesinghe, Nayomi Kankanamge, Tan Yigitcanlar () and Surabhi Pancholi
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Sandulika Abesinghe: Department of Town and Country Planning, University of Moratuwa, Katubedda, Moratuwa 10400, Sri Lanka
Nayomi Kankanamge: Department of Town and Country Planning, University of Moratuwa, Katubedda, Moratuwa 10400, Sri Lanka
Tan Yigitcanlar: City 4.0 Lab, School of Architecture and Built Environment, Queensland University of Technology, Brisbane, QLD 4000, Australia
Surabhi Pancholi: School of Architecture and Built Environment, Deakin University, Geelong, VIC 3220, Australia

Future Internet, 2023, vol. 15, issue 1, 1-21

Abstract: The image of a city represents the sum of beliefs, ideas, and impressions that people have of that city. Mostly, city images are assessed through direct or indirect interviews and cognitive mapping exercises. Such methods consume more time and effort and are limited to a small number of people. However, recently, people tend to use social media to express their thoughts and experiences of a place. Taking this into consideration, this paper attempts to explore city images through social media big data, considering Colombo, Sri Lanka, as the testbed. The aim of the study is to examine the image of a city through Lynchian elements—i.e., landmarks, paths, nodes, edges, and districts—by using community sentiments expressed and images posted on social media platforms. For that, this study conducted various analyses—i.e., descriptive, image processing, sentiment, popularity, and geo-coded social media analyses. The study findings revealed that: (a) the community sentiments toward the same landmarks, paths, nodes, edges, and districts change over time; (b) decisions related to locating landmarks, paths, nodes, edges, and districts have a significant impact on community cognition in perceiving cities; and (c) geo-coded social media data analytics is an invaluable approach to capture the image of a city. The study informs urban authorities in their placemaking efforts by introducing a novel methodological approach to capture an image of a city.

Keywords: city image; Lynchian elements; image processing; sentiment analysis; social media analytics; urban analytics; big data analytics; urban informatics; Colombo; Sri Lanka (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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