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    Where Am I? Location Archetype Keyword Extraction from Urban Mobility Patterns

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    Author
    Kostakos, V; Juntunen, T; Goncalves, J; Hosio, S; Ojala, T
    Date
    2013-05-21
    Source Title
    PLoS One
    Publisher
    PUBLIC LIBRARY SCIENCE
    University of Melbourne Author/s
    Kostakos, Vassilis; Goncalves, Jorge
    Affiliation
    Computing and Information Systems
    Metadata
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    Document Type
    Journal Article
    Citations
    Kostakos, V., Juntunen, T., Goncalves, J., Hosio, S. & Ojala, T. (2013). Where Am I? Location Archetype Keyword Extraction from Urban Mobility Patterns. PLOS ONE, 8 (5), https://doi.org/10.1371/journal.pone.0063980.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/258183
    DOI
    10.1371/journal.pone.0063980
    Abstract
    Can online behaviour be used as a proxy for studying urban mobility? The increasing availability of digital mobility traces has provided new insights into collective human behaviour. Mobility datasets have been shown to be an accurate proxy for daily behaviour and social patterns, and behavioural data from Twitter has been used to predict real world phenomena such as cinema ticket sale volumes, stock prices, and disease outbreaks. In this paper we correlate city-scale urban traffic patterns with online search trends to uncover keywords describing the pedestrian traffic location. By analysing a 3-year mobility dataset we show that our approach, called Location Archetype Keyword Extraction (LAKE), is capable of uncovering semantically relevant keywords for describing a location. Our findings demonstrate an overarching relationship between online and offline collective behaviour, and allow for advancing analysis of community-level behaviour by using online search keywords as a practical behaviour proxy.

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