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- W3128774420 abstract "Geospatially located social media data is increasingly used to understand human behaviour. This flow of social activity can offer a real time understanding of cities and provide insight into many issues such as estimations of crowd sizes, urban planning or even criminal activity. In this paper we combine a multitude of social media data from diverse social media platforms to explore population movement patterns and activities in two major cities in Australia (Melbourne and Sydney). We provide a framework for the identification of clusters of activity and explore different temporal patterns and compare them with historical averages in order to distinguish anomalous activity. We also utilize natural language processing of the geo-textual data as well as supervised machine learning to classify the use of locations based on clusters of activity. Collectively these analyses offer insight into urban human activity to provide a city pulse." @default.
- W3128774420 created "2021-02-15" @default.
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- W3128774420 date "2020-12-14" @default.
- W3128774420 modified "2023-09-26" @default.
- W3128774420 title "Using Social Media to Understand City-wide Movement Patterns and Behaviours" @default.
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- W3128774420 doi "https://doi.org/10.1109/snams52053.2020.9336560" @default.
- W3128774420 hasPublicationYear "2020" @default.
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