Research on Facebook (and other
social networks)
Welcome. My group has been studying online social networks with a primary focus on Facebook. Facebook is currently the largest online social network, with more than 200 million active users worldwide (April 2009). It is also an interesting and vibrant application platform for everything from shared Netflix reviews to Hugg and social marketplaces.
We have also worked on a number of other social networking topics, including a measurement of the socially-enhanced Overstock.com auction site, and a system for using social networks to protect anonymous communication users from passive traffic analysis attacks.
Related Publications:
- StarClique: Guaranteeing User Privacy in Social
Networks Against Intersection Attacks,
Krishna P. N. Puttaswamy, Alessandra Sala, and Ben Y. Zhao
To Appear: Proceedings of ACM Conference on emerging Networking EXperiments and Technologies (CoNEXT), Rome, Italy, December 2009.
- User
Interactions in Social Networks and their Implications,
Christo Wilson, Bryce Boe, Alessandra Sala, Krishna P. N. Puttaswamy and Ben Y. Zhao
Proceedings of ACM EuroSys, Nuremburg, Germany, April 2009.
- Improving Anonymity using Social Links,
Krishna P. N. Puttaswamy, Alessandra Sala and Ben Y. Zhao
Proceedings of IEEE Workshop on Secure Network Protocols (NPSec 2008), Orlando, FL, October 2008.
- Can Social Networks Improve e-Commerce: a Study on Social
Marketplaces,
Gayatri Swamynathan, Christo Wilson, Bryce Boe, Kevin C. Almeroth and Ben Y. Zhao.
Proceedings of First SIGCOMM Workshop on Online Social Networks (WOSN 2008), Seattle, WA, August 2008.
Datasets:
Following our EuroSys Facebook measurement study, we are making some datasets of social graphs and interaction graphs available.
These graphs only contain simple edges connecting anonymized nodeIDs. The social graph file is simply a list of all edges in the graph, each bidirectional edge represented by a two-tuple of anonymized nodeIDs. Our user connectivity graphs reflect measurements performed in early 2008, and are not reflective of current Facebook topologies.
For the anonymized interaction graphs, we filter interactions based on their relative age to the time of the crawl (April 2008). Each edge in the interaction graph is listed in the file as a two-tuple of anonymized nodeIDs. The interaction graph is an undirected graph, so an edge from A to B represents a bidirectional edge connecting them. We include multiple interactions within the same period as duplicate edges across the same endpoints to account for user pairs that interact more than once during the time period. This frequency can be used to assign "weights" to edges on the interaction graph. If you want an undirected, unweighted interaction graph, then remove those duplicate edges.
Note: If you would like access to this data, please send email to ravenben at cs dot ucsb dot edu. When you get access to the data files, please do not distribute them beyond your immediate research group. Thank you.
- Anonymized social graphs
- Anonymous regional network A: 3,097,166 users, 28,377,481 edges, 605MB GZipped
- Anonymous regional network B: 2,937,614 users, 24,236,701 edges, 521MB GZipped
- Anonymized interaction graphs
- Anonymous regional network A, n=1, t=1 month: 1,412,252 interactions, 22MB GZipped
- Anonymous regional network A, n=1, t=1/2 year: 7,483,904 interactions, 87MB GZipped
- Anonymous regional network A, n=1, t=1 year: 16,889,111 interactions, 159MB GZipped
- Anonymous regional network A, n=1, t=lifetime: 17,644,327 interactions, 164MB GZipped