Location Contexts of User Check-Ins to Model Urban Geo Life-Style Patterns

Geo-location data from social media offers us information, in new ways, to understand people's attitudes and interests through their activity choices. In this paper, we explore the idea of inferring individual life-style patterns from activity-location choices revealed in social media. We prese...

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Veröffentlicht in:PloS one Jg. 10; H. 5; S. e0124819
Hauptverfasser: Hasan, Samiul, Ukkusuri, Satish V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Public Library of Science 13.05.2015
Public Library of Science (PLoS)
Schlagworte:
Analysis
Behavior
Choice Behavior
Coexistence
Computer Simulation
Datasets
Digital media
Friendship
Geographic Information Systems
Humans
International conferences
Knowledge management
Life Style
Location based services
Models, Statistical
Neighborhoods
New York City
Participation
Place preferences
Role models
Smartphones
Social Media
Social networks
Social research
Sociodemographics
Studies
Urban Population
New York City
New York
ISSN:1932-6203, 1932-6203
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Zusammenfassung:Geo-location data from social media offers us information, in new ways, to understand people's attitudes and interests through their activity choices. In this paper, we explore the idea of inferring individual life-style patterns from activity-location choices revealed in social media. We present a model to understand life-style patterns using the contextual information (e. g. location categories) of user check-ins. Probabilistic topic models are developed to infer individual geo life-style patterns from two perspectives: i) to characterize the patterns of user interests to different types of places and ii) to characterize the patterns of user visits to different neighborhoods. The method is applied to a dataset of Foursquare check-ins of the users from New York City. The co-existence of several location contexts and the corresponding probabilities in a given pattern provide useful information about user interests and choices. It is found that geo life-style patterns have similar items-either nearby neighborhoods or similar location categories. The semantic and geographic proximity of the items in a pattern reflects the hidden regularity in user preferences and location choice behavior.
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Conceived and designed the experiments: SH SVU. Performed the experiments: SH. Analyzed the data: SH. Contributed reagents/materials/analysis tools: SH SVU. Wrote the paper: SH SVU.
Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0124819