Abstract
Interactive visualization systems are powerful tools in the task of exploring and understanding data. We describe two implementations of this approach, where a multidimensional network of news clips is depicted by taking advantage of its community structure. The first implementation is a multiresolution map of news clips that uses topic detection both at the clip level and at the community level, in order to assign labels to the nodes in each resolution. The second implementation is a traditional force-directed network visualization with several additional interactive aspects that provide a rich user experience for knowledge discovery. We describe a common use case for the visualization systems as a journalistic research and knowledge discovery tool. Both systems illustrate the links between news clips, induced by the co-occurrence of named entities, as well as several metadata fields based on the information contained within each node. Copyright © 2012 SciTePress - Science and Technology Publications.

Abstract
The study of the blogosphere can provide sociologically relevant data. We analyze the links between blogs in the portuguese blogosphere, in order to understand how they group and interact, to identify clusters and to characterize them. Our data set contains post data for more than 70,000 blogs, with over 400,000 links. The linkage data is represented as a blog graph and partitioned into several slices, according to their in-degree. We then study the evolution of blog features, and observe a consistent pattern of decrease in posting frequency, number of out-links, and post length, as we move from the highly-cited blogs to the less cited ones. Copyright 2010 ACM.

Abstract
We build and analyze a coreference network based on entities from photo descriptions, where nodes represent personalities and edges connect people mentioned in the same photo description. We identify and characterize the communities in this network and propose taking advantage of the context provided by community detection methodologies to improve text illustration and general search. © 2012 Springer-Verlag Berlin Heidelberg.

Abstract

Abstract
This paper describes the participation of FEUP, from the University of Porto, in the TREC 2010 Blog Track. FEUP participated in the baseline blog distillation task with work focused on the use of link features available in the TREC Blogs08 collection. The approach presented in this paper uses the link information available in most individual posts to amplify each post's score. Blog scores, and subsequent ranks, are obtained by combining individual post scores. We boost post scores using the in-degree of each post and the h-index of each blog. This results in an improvement of P@10, over our baseline, for the in-degree and the h-index runs. When compared to the in- degree, the h-index run results in higher performance values for each of the applied evaluation metrics.