Social Networks Analysis

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Online social networks have revolutionized the way we interact and share information over the Internet. Popular social networking applications include Facebook, LinkedIn and Twitter, which support millions of active users. While being enormously popular, we believe hat that these applications only scratch the surface of what is possible to do and that there are tremendous opportunities in developing new and more advanced online social networking applications.***Developing such applications and algorithms poses new and fascinating research problems. The major research challenge is to develop a formal understanding of online social networks both in terms of how these networks are formed and evolve over time, as well as how they can be used to efficiently share and distribute information. The goal of the proposed research is to address these challenges by working towards a theoretical foundation of social networks. As such, the focus of the proposed research program is on creating mathematical models for how social networks are being formed and used to shared and distribute information.***We believe that a formal understanding of how social networks are being formed and used to share and distribute information can lead to fundamentally new algorithms both for social networking analysis and the implementation of social networking applications. In particular, the striking feature of social networks is that there exists a strong coupling between the network topology and the information flow within the network. We believe that by quantitatively modeling and analyzing this relation, it is possible to design algorithms that are simpler and are more efficient compared with existing algorithms, and yet lead to (close) to optimal performance.***The proposed research has the potential to have an impact both on the academic research community and for practical social networking applications. On one hand, creating a mathematical models that can be used derive properties of social network and to derive social network analysis algorithms will deepen the understanding of social networks. On the other hand, this understanding can also be used to create and design novel online social networking applications that go well beyond of what today's social networking applications are capable of doing. In particular, we envision new social networking application that are able to interact with more naturally, and are able to more accurately filter the content that users are interested in. This is in contrast with the large amount of noise that exists in today's social network application such as Twitter.**