Abstract
On line social networks (e.g., Facebook, Twitter) allow users to tag their posts with geographical coordinates collected through the GPS interface of smart phones. The time- and geo-coordinates associated with a sequence of tweets manifest the spatial-temporal movements of people in real life. This paper aims to analyze such movements to discover people and community behavior. To this end, we defined and implemented a novel methodology to mine popular travel routes from geo-tagged posts. Our approach infers interesting locations and frequent travel sequences among these locations in a given geo-spatial region, as shown from the detailed analysis of the collected geo-tagged data.
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Comito, C., Falcone, D., Talia, D. (2015). Mining Popular Travel Routes from Social Network Geo-Tagged Data. In: Damiani, E., Howlett, R., Jain, L., Gallo, L., De Pietro, G. (eds) Intelligent Interactive Multimedia Systems and Services. Smart Innovation, Systems and Technologies, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-319-19830-9_8
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DOI: https://doi.org/10.1007/978-3-319-19830-9_8
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