In this work, we investigate the use of online or “crawling” algorithms to sample large social networks in order to determine the most influential or important individuals wit...
State-of-the-art techniques for probability sampling of users of online social networks (OSNs) are based on random walks on a single social relation. While powerful, these methods ...
Minas Gjoka, Carter T. Butts, Maciej Kurant, Athin...
As online social networking emerges, there has been increased interest to utilize the underlying social structure as well as the available social information to improve search. In...
Gautam Das, Nick Koudas, Manos Papagelis, Sushruth...
Activity and user engagement in social media such as web logs, wikis, online forums or social networks has been increasing at unprecedented rates. In relation to social behavior i...
We design two different strategies for computing the unknown content preferences in an online social network based on a small set of nodes in the corresponding social graph for wh...