Tag Archives: gowalla

A Friend Like Me: Modeling Network Formation in a Location-Based Social Network (JMIS 2016)

Lee, Gene Moo*, Liangfei Qiu*, Andrew B. Whinston* (2016) A Friend Like Me: Modeling Network Formation in a Location-Based Social Network, Journal of Management Information Systems 33(4), pp. 1008-1033. (* equal contribution)

  • Best Paper Nomination at HICSS 2016
  • Presented in WITS (Auckland, New Zealand 2014), and WISE (Auckland, New Zeland 2014), HICSS (Kauai, HI 2016)
  • Dissertation Paper #2

This article studies the strategic network formation in a location-based social network. We build an empirical model of social link creation that incorporates individual characteristics and pairwise user similarities. Specifically, we define four user proximity measures from biography, geography, mobility, and short messages. To construct proximity from unstructured text information, we build topic models using Latent Dirichlet Allocation. Using Gowalla data with 385,306 users, 3 million locations, and 35 million check-in records, we empirically estimate the model to find evidence on the homophily effect on network formation. To cope with possible endogeneity issues, we use exogenous weather shocks as our instrumental variables and find the empirical results are robust: network formation decisions are significantly affected by our proximity measures.

Strategic Network Formation in a Location-Based Social Network: A Topic Modeling Approach (HICSS 2016)

Lee, G. M., Qiu, L., Whinston, A. B. (2016). Strategic Network Formation in a Location-Based Social Network: A Topic Modeling Approach, Proceedings of Hawaii International Conference on System Sciences (HICSS 2016), Kauai, Hawaii. Nominated for Best Paper Award

This paper studies strategic network formation in a location-based social network. We build a structural model of social link creation that incorporates individual characteristics and pairwise user similarities. Specifically, we define four user proximity measures from biography, geography, mobility, and short messages. To construct proximity from unstructured text information, we build topic models using latent Dirichlet allocation. Using Gowalla data with 385,306 users, three million locations, and 35 million check-in records, we empirically estimate the structural model to find evidence on the homophily effect in network formation.

Mobile Video Delivery via Human Movement (SECON 2013)

Lee, G. M., Rallapalli, S., Dong, W., Chen, Y., Qiu, L., and Zhang, Y. (2013). Mobile Video Delivery via Human Movement. In Proceedings of IEEE Conference on Sensor, Mesh, and Ad Hoc Communications and Networks (SECON 2013), New Orleans, Louisiana.

  • SECON is a premier conference in the networking area (h-index: 22)

This paper proposes VideoFountain, a novel service that deploys kiosks at popular venues to store and transmit digital media to users’ personal devices using Wi-Fi access points, which may not have Internet connectivity. We leverage mobile users to deliver content to these kiosks. A key component in this design is an in-depth understanding of user mobility. We gather real mobility traces from two largest location-based social networks (Foursquare and Gowalla) and analyze both macroscopic and microscopic human mobility in different cities. Based on the insights we gain, we study several algorithms to determine the initial placement of content and design routing algorithms to optimize content delivery. We further consider several practical issues, such as how to incentivize users to forward content, how to manage copyrights, how to ensure security, and how to achieve service discovery. We demonstrate the feasibility of VideoFountain using trace-driven simulations.