Learn More
etworks have become ubiquitous. Communication networks, financial transaction networks, networks describing physical systems, and social networks are all becoming increasingly important in our day-today life. Often, we are interested in models of how nodes in the network influence each other (for example, who infects whom in an epidemiological network),(More)
In recent years, informal, online communication has transformed the ways in which we connect and collaborate with friends and colleagues. With millions of individuals communicating online each day, we have a unique opportunity to observe the formation and evolution of roles and relationships in networked groups and organizations. Yet a number of challenges(More)
The problems of object classification (labeling the nodes of a graph) and link prediction (predicting the links in a graph) have been largely studied independently. Commonly , object classification is performed assuming a complete set of known links and link prediction is done assuming a fully observed set of node attributes. In most real world domains,(More)
This work investigates design choices in modeling a discourse scheme for improving opinion polarity classification. For this, two diverse global inference paradigms are used: a supervised collective classification framework and an un-supervised optimization framework. Both approaches perform substantially better than baseline approaches, establishing the(More)
This paper describes a computational approach to resolving the true referent of a named mention of a person in the body of an email. A generative model of mention generation is used to guide mention resolution. Results on three relatively small collections indicate that the accuracy of this approach compares favorably to the best known techniques, and(More)
—There is a growing interest in methods for analyzing data describing networks of all types, including information, biological, physical, and social networks. Typically the data describing these networks is observational, and thus noisy and incomplete; it is often at the wrong level of fidelity and abstraction for meaningful data analysis. This has resulted(More)
Online communications provide a rich resource for understanding social networks. Information about the actors, and their dynamic roles and relationships, can be inferred from both the communication content and traffic structure. A key component in the analysis of online communications such as email is the resolution of name references within the body of the(More)
This work shows how to construct discourse-level opinion graphs to perform a joint interpretation of opinions and discourse relations. Specifically, our opinion graphs enable us to factor in discourse information for polarity classification, and polarity information for discourse-link classification. This interdependent framework can be used to augment and(More)
Visualizing network data, from tree structures to arbitrarily connected graphs, is a difficult problem in information visualization. A large part of the problem is that in network data, users not only have to visualize the attributes specific to each data item, but also the links specifying how those items are connected to each other. Past approaches to(More)