9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

Research Article

Understanding Venue Popularity in Foursquare

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2013.254258,
        author={Xuelian Long and Lei jin and James Joshi},
        title={Understanding Venue Popularity in Foursquare},
        proceedings={9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing},
        publisher={ICST},
        proceedings_a={COLLABORATECOM},
        year={2013},
        month={11},
        keywords={location-based social network venue popularity foursquare},
        doi={10.4108/icst.collaboratecom.2013.254258}
    }
    
  • Xuelian Long
    Lei jin
    James Joshi
    Year: 2013
    Understanding Venue Popularity in Foursquare
    COLLABORATECOM
    IEEE
    DOI: 10.4108/icst.collaboratecom.2013.254258
Xuelian Long1, Lei jin1, James Joshi1,*
  • 1: School of Information Sciences University of Pittsburgh
*Contact email: jjoshi@pitt.edu

Abstract

Recently, social media has become an increasingly important part of business and marketing. More and more businesses use social media as part of their marketing platforms. Moreover, the fast development of the 4th generation mobile network and the ubiquity of the advanced mobile devices in which GPS modules are embedded promote the location-based services. Location-based social networks (LBSNs), as the combination of mobile, location-based service and social media, have been changing the way customers interact with the physical location of a business. Foursquare is one of such popular LBSNs in which a user can check in at his current location, leave tips about the venue, explore discounts around his current location, add other people as his friends and so on. These services provide more information to users on where to eat, shop and go for entertainment, as well as a platform to share their activities with their friends. In this paper, we analyze the Foursquare data pertaining to greater Pittsburgh area to investigate several interesting features that could impact venue popularity. By extracting various information in LBSNs, we investigate which are the popular venues, what kind of venues are popular, and what makes them popular. In particular, we study the local hot spots that indicate users’ preferences of venues. We also explore if the special offers and web presence help venues become more popular in general. We also analyze trending venues (i.e., very popular venues at a certain time) to investigate the influence of these features on venue popularity over time. Our quantitative analysis could be used to help business owners to design better marketing strategies in LBSNs.