Articlediamond2014

EXTRACTING HUMAN BEHAVIORAL PATTERNS BY MINING GEO-SOCIAL NETWORKS

Mohammad Ali Forghani · Farid Karimipour

3 citations0/0 files storedThe international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences

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Human Mobility and Location-Based Analysis Geographic Information Systems Studies Data Management and Algorithms

Abstract

Abstract. Accessibility of positioning technologies such as GPS offer the opportunity to store one’s travel experience and publish it on the web. Using this feature in web-based social networks and considering location information shared by users as a bridge connecting the users’ network to location information layer leads to the formation of Geo-Social Networks. The availability of large amounts of geographical and social data on these networks provides rich sources of information that can be utilized for studying human behavior through data analysis in a spatial-temporal-social context. This paper attempts to investigate the behavior of around 1150 users of Foursquare network by making use of their check-ins. The authors analyzed the metadata associated with the whereabouts of the users, with an emphasis on the type of places, to uncover patterns across different temporal and geographical scales for venue category usage. The authors found five groups of meaningful patterns that can explore region characteristics and recognize a number of major crowd behaviors that recur over time and space.

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References

2012Discovering regions of different functions in a city using human mobility and POIs 2009Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network 2021Exploring Social-Historical Ties on Location-Based Social Networks 2012Characterizing Urban Landscapes Using Geolocated Tweets 2009Measuring serendipity 2011Extracting urban patterns from location-based social networks 2009Analysis of a Location-Based Social Network 2013Mining user behaviours

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