Abstract
The availability of location-based agent data is growing rapidly, enabling new research into the behavior patterns of such agents in space and time. Previously, such analysis was limited to either small experiments with GPS-equipped agents, or proprietary datasets of human cell phone users that cannot be disseminated across the academic community for followup studies. In this paper, we study the movement patterns of Twitter users in London, Los Angeles, and Tokyo. We cluster these agents by their movement patterns across space and time. We also show that it is possible to infer part of the underlying transportation net- work from Tweets alone, and uncover interesting differences between the behaviors exhibited by users across these three cities.
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Azmandian, M., Singh, K., Gelsey, B., Chang, YH., Maheswaran, R. (2013). Following Human Mobility Using Tweets. In: Cao, L., Zeng, Y., Symeonidis, A.L., Gorodetsky, V.I., Yu, P.S., Singh, M.P. (eds) Agents and Data Mining Interaction. ADMI 2012. Lecture Notes in Computer Science(), vol 7607. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36288-0_13
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DOI: https://doi.org/10.1007/978-3-642-36288-0_13
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