Where Am I? Location Archetype Keyword Extraction from Urban Mobility Patterns
AuthorKostakos, V; Juntunen, T; Goncalves, J; Hosio, S; Ojala, T
Source TitlePLoS One
PublisherPUBLIC LIBRARY SCIENCE
AffiliationComputing and Information Systems
Document TypeJournal Article
CitationsKostakos, 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 StatusOpen Access
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.
- Click on "Export Reference in RIS Format" and choose "open with... Endnote".
- Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References