Using social media data for urban analysis in Singapore

• Main Author: Koh, Wee Boon
• Other Authors: Cong Gao
• Format: Theses and Dissertations
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing; DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
• Online Access: http://hdl.handle.net/10356/73050
• Institution: Nanyang Technological University

Effective land use planning is essential for countries where land is scarce. In Singapore, land use planning is managed by the Urban Redevelopment Authority (URA). A revised land use plan is released by the URA every four to five years with the goal to create self-sufficient neighbourhoods and reduce commute time between places. Identifying identical land zones can assist city planners to draft out similar development objectives, reducing the time required to produce the land use plan. For business owners, identifying similar land zones can allow them to find the next potential area of expansion that fits their first success case. This work provides an analysis and a framework to the problem of similar urban region query. In particular, the analysis and the proposed query framework investigate the use of urban and social media data to find regions that are topically consistent and exhibits similar demographics. To achieve this, an Urban Region Similarity Analysis System (URSAS) is developed. This work shows that social media data can help to improve the quality of the query result as opposed to only considering urban information. Additionally, this work shows that the proposed query framework can recognize the type of function for a given zone based on urban and social media data.