Location based Social Networks (LBSN) are a special type of online social networks where the location dimension is added that helps to bridge the gap between the physical world and online social networking services. Customers in a popular LBSN such as Foursquare, Yelp, etc. can share location-tagged information about visited businesses through various modalities such as check-ins and user generated textual comments. LBSNs also consist of the new social structure made up of customers connected by the interdependency derived from their locations in the physical world as well as their location-tagged media content. In general, LBSNs deal with two major players, namely, business owners, who establish and run business units in different parts of a city, and customers who visit those business units.
Our research group mainly focuses on the application of the user generated contents such as tips and reviews in LBSNs. For instance, tips and reviews posted by customers in Yelp, a popular LBSN, to share their experiences of visited businesses provide complementary information about customers’ interests and can be used for recommending visits to future businesses. Further, such textual modalities in Yelp can be utilized to identify important factors that drive customers to businesses thus contributing to their popularity.
- Ayan Kumar Bhowmick, Sourav Suman and Bivas Mitra, “Effect of Information Propagation on Business Popularity: A Case Study on Yelp”, in Proceedings of the 18th IEEE International Conference on Mobile Data Management, IEEE MDM 2017, 29 May – 1 June, 2017, KAIST, Daejeon, South Korea.
- Utpal Prasad, Nikky Kumari, Niloy Ganguly, Mohit Kumar, Animesh Mukherjee, “The role of outsiders in consensus formation: A case study of Yelp”, in Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion (CSCW’16 Companion), February 26 – March 02, 2016, San Francisco, California, USA.
- Saurabh Gupta, Bivas Mitra, Sayan Pathak, “Complementary usage of Tips and Reviews for Location Recommendation in Yelp”, in Proceedings of Pacific-Asiaconference on Knowledge Discovery and Data Mining (PAKDD 2015), Ho Chi Minh City, Vietnam, – 07.02.2015.
- Ayan Kumar Bhowmick’s paper “Effect of Information Propagation on Business Popularity: A Case Study on Yelp” won the Best Student Paper award at IEEE MDM 2017.
Members & Collaborations
- Niloy Ganguly
- Bivas Mitra
- Animesh Mukherjee
- Ayan Kumar Bhowmick