Abstract
The general available tools for analyzing interactions in online discussion forums appear to be insufficient to characterize groups of medium/large dimensions, as they are limited to provide general information of participation, access statistics and message posting. Our research contributes for analyzing and characterizing asynchronous online interactions applying the Social Network Analysis methodology, by providing e-learning platforms with an interactive graph - the iGraph - that illustrates, and analyses, students' interactions. In a graphical interface embedded in an open source learning management system we combine real-time graphs and numerical indicator to provide the educator with a more thorough understanding of relations between course participants. Preliminary results indicate that the iGraph enables an insightful characterization of the interactions between actors and their participations in discussion forums.

Abstract
Current Learning Management Systems generically provide online forums for interactions between students and educators. In this article we propose a tool, the iGraph, that can be embedded in Learning Management Systems that feature hierarchical forums. The iGraph is capable of depicting and analyzing online interactions in an easy to understand graph. The positioning algorithm is based on social network analysis statistics, taken from the collected interactions, and is able to smoothly present temporal evolution in order to find communicational patterns and report them to the educator.

Abstract
Computational journalism allows journalists to collect large collections of information chunks from separate sources. The analysis of these collections can reveal hidden relationships between of relationships, but due to their size, diversity, and varying nuances it is necessary to use both computational and human analysis. Breadcrumbs PDL is an adaptive spatial hypermedia system that brings together human cognition and machine computation in order to analyze a collection of usergenerated news clips. The project demonstrates the effectiveness of spatial hypermedia in the domain of computational journalism.

Abstract
Breadcrumbs is a folksonomy of news clips, where users can aggregate fragments of text taken from online news. Besides the textual content, each news clip contains a set of metadata fields associated with it. User-defined tags are one of the most important of those information fields. Based on a small data set of news clips, we build a network of cooccurrence of tags in news clips, and use it to improve text clustering. We do this by defining a weighted cosine similarity proximity measure that takes into account both the clip vectors and the tag vectors. The tag weight is computed using the related tags that are present in the discovered community. We then use the resulting vectors together with the new distance metric, which allows us to identify socially biased document clusters. Our study indicates that using the structural features of the network of tags leads to a positive impact in the clustering process. Copyright 2012 ACM.

Abstract
Discussion forums are presently one of the most important tools in assisting distance education. Web learning is accomplished by using these communication tools and, particularly, by the interactions that take place in these settings. Therefore, students' participations in a discussion forum, the frequency and the way they participate, the types of interactions that they create with their colleagues and with the professor, can and should be analyzed in order to fully understand the group and, consequently, allow a more efficient and student focused education. In this article, suggest graphical representations (the iGraph) of these interactions and by using these tools, we describe forum participation according to the centralization of information, the density and intensity of interactions, and yet the quality of the moderation.

Abstract
In this article we describe a system that is capable of self-organizing news clips collected by readers, into a personal digital library. The system then uses this information to provide a rich set of inferred relations between the clips and clusters of clips to the producers. The inferred information is in the form of news with the 'hot' topics, the relations between clips content and the interests of their readers. We describe the Breadcrumbs system which features an online news collecting tool, an inference engine and a social graph. We discuss the outcomes of our system, which allows for a better understanding of the news consumption and trends. Finally, we describe how we can use these outcomes to create a business model. © 2012 IEEE.