Konstantin Mertsalov

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—Increasingly, methods to identify community structure in networks have been proposed which allow groups to overlap. These methods have taken a variety of forms, resulting in a lack of consensus as to what characteristics overlapping communities should have. Furthermore, overlapping community detection algorithms have been justified using intuitive(More)
—We study information diffusion in real-life and synthetic dynamic networks, using well known threshold and cascade models of diffusion. Our test-bed is the communication network of the LiveJournal Blogosphere. We observe that the dynamic and static versions of the Blogograph, yield very different behaviors of the diffusion. It was earlier discovered that(More)
We study the communication dynamics of Blog networks, focusing on the Russian section of LiveJournal as a case study. Communications (blogger-to-blogger links) in such online communication networks are very dynamic: over 60% of the links in the network are new from one week to the next, though the set of bloggers remains approximately constant. Two(More)
Identifying communities is essential for understanding the dynamics of a social network. The prevailing approach to the problem of community discovery is to partition the network into disjoint groups of members that exhibit a high degree of internal communication. This approach ignores the possibility that an individual may belong to two or more groups.(More)
The primary focus of this paper is to describe stable statistics of the blogosphere's evolution which convey information on the social network's dynamics. In this paper, we present a number of non-trivial statistics that are surprisingly stable and thus can be used as benchmarks to diagnose phase-transitions in the network. We believe that stable statistics(More)
—We present a model of evolution of large social networks. Our model is based on the local nature of communication: a node's communication energy is spend mostly within it's small social area. We test our model on the Blog network hosted by LiveJournal. Our testing with different definitions of local areas shows that the best approximation to the observed(More)
3 Abstract—We present an extended version of a software system SIGHTS 1 (Statistical Identification of Groups Hidden in Time and Space), which can be used for the discovery, analysis, and knowledge visualization of social coalitions in communication networks such as Blog-networks. The evolution of social groups reflects information flow and social dynamics(More)
—This work experimentally examines different notions of stability of the behavior of individuals and groups in a network of blogs. Our experiments are conducted on data collected from LiveJournal. All stability notions aim to locate stable behavior within an individual's area, which is defined in a variety of manners. Our experiments confirm an earlier(More)
—In this work, we present the software library graphOnt. The purpose of this library is to automate the process of dynamically extracting " interesting " graphs from semantic networks. Instructions on the extraction are fed into the library via an ontological language specification custom built for this application. A set of SPARQL queries are used to(More)
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