This paper describes methods for collecting user activity data in a peer production educational system, the Instructional Architect (IA), and then takes a social network perspectiv...
A trust metric is a technique for predicting how much a user of a social network might trust another user. This is especially beneficial in situations where most users are unknown ...
The current methods used to mine and analyze temporal social network data make two assumptions: all edges have the same strength, and all parameters are time-homogeneous. We show ...
Abstract--As research into community finding in social networks progresses, there is a need for algorithms capable of detecting overlapping community structure. Many algorithms hav...
Online social networking sites like Orkut, YouTube, and Flickr are among the most popular sites on the Internet. Users of these sites form a social network, which provides a power...
Alan Mislove, Massimiliano Marcon, P. Krishna Gumm...
Abstract. Closeness centrality is an important concept in social network analysis. In a graph representing a social network, closeness centrality measures how close a vertex is to ...
We have developed a computational framework to characterize social network dynamics in the blogosphere at individual, group and community levels. Such characterization could be us...
Munmun De Choudhury, Hari Sundaram, Ajita John, Do...
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Multimedia ranking algorithms are usually user-neutral and measure the importance and relevance of documents by only using the visual contents and meta-data. However, users’ int...
Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolon...
In search engines, ranking algorithms measure the importance and relevance of documents mainly based on the contents and relationships between documents. User attributes are usual...