Modeling and Studying Online Social Networks

Online Social Networks are gradually gaining a ever more prominent place in both our online and offline lives. Through them we can interact with our closest friends and the faintest of our acquaintances. Such interactions can take many forms, from direct conversations to online “poking” or sharing of media, but they all leave a digital footprint that is now starting to proving insights into the nature of human interactions. Using data from Twitter, Yahoo! Meme, Google Buzz, etc… and analytical and computational modeling we strive to obtain a broader view of the way people interact and exchange information. What can we learn from these new detailed sources of data about human behavior? Why do certain pieces of information (videos, rumors, jokes, etc…) spread from person to person? How does the dynamics of the users help shape the systems themselves? Can we use them to get the pulse of society? And how can these new insights guide us in the development of better communication and information infrastructures?

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