Publication Type

Conference Proceeding Article

Publication Date

10-2016

Abstract

Modeling user check-in behavior provides useful insights about venues as well as the users visiting them. These insights can be used in urban planning and recommender system applications. Unlike previous works that focus on modeling distance effect on user’s choice of check-in venues, this paper studies check-in behaviors affected by two venue-related factors, namely, area attractiveness and neighborhood competitiveness. The former refers to the ability of an area with multiple venues to collectively attract checkins from users, while the latter represents the ability of a venue to compete with its neighbors in the same area for check-ins. We first embark on a data science study to ascertain the two factors using two Foursquare datasets gathered from users and venues in Singapore and Jakarta, two major cities in Asia. We then propose the VAN model incorporating user-venue distance, area attractiveness and neighborhood competitiveness factors. The results from real datasets show that VAN model outperforms the various baselines in two tasks: home location prediction and check-in prediction.

Keywords

Area attractiveness, Location-based social network, Neighborhood competition, Singapore, Jakarta

Discipline

Computer Sciences | Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

CIKM 2016: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management: Indianapolis, October 24-28, 2016

First Page

2149

Last Page

2154

ISBN

9781450340731

Identifier

10.1145/2983323.2983657

Publisher

ACM

City or Country

New York

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1145/2983323.2983657

Share

COinS