3,284 research outputs found
CitNetExplorer: A new software tool for analyzing and visualizing citation networks
We present CitNetExplorer, a new software tool for analyzing and visualizing
citation networks of scientific publications. CitNetExplorer can for instance
be used to study the development of a research field, to delineate the
literature on a research topic, and to support literature reviewing. We first
introduce the main concepts that need to be understood when working with
CitNetExplorer. We then demonstrate CitNetExplorer by using the tool to analyze
the scientometric literature and the literature on community detection in
networks. Finally, we discuss some technical details on the construction,
visualization, and analysis of citation networks in CitNetExplorer
Spectral goodness of fit for network models
We introduce a new statistic, 'spectral goodness of fit' (SGOF) to measure
how well a network model explains the structure of an observed network. SGOF
provides an absolute measure of fit, analogous to the standard R-squared in
linear regression. Additionally, as it takes advantage of the properties of the
spectrum of the graph Laplacian, it is suitable for comparing network models of
diverse functional forms, including both fitted statistical models and
algorithmic generative models of networks. After introducing, defining, and
providing guidance for interpreting SGOF, we illustrate the properties of the
statistic with a number of examples and comparisons to existing techniques. We
show that such a spectral approach to assessing model fit fills gaps left by
earlier methods and can be widely applied
Time-Varying Graphs and Dynamic Networks
The past few years have seen intensive research efforts carried out in some
apparently unrelated areas of dynamic systems -- delay-tolerant networks,
opportunistic-mobility networks, social networks -- obtaining closely related
insights. Indeed, the concepts discovered in these investigations can be viewed
as parts of the same conceptual universe; and the formal models proposed so far
to express some specific concepts are components of a larger formal description
of this universe. The main contribution of this paper is to integrate the vast
collection of concepts, formalisms, and results found in the literature into a
unified framework, which we call TVG (for time-varying graphs). Using this
framework, it is possible to express directly in the same formalism not only
the concepts common to all those different areas, but also those specific to
each. Based on this definitional work, employing both existing results and
original observations, we present a hierarchical classification of TVGs; each
class corresponds to a significant property examined in the distributed
computing literature. We then examine how TVGs can be used to study the
evolution of network properties, and propose different techniques, depending on
whether the indicators for these properties are a-temporal (as in the majority
of existing studies) or temporal. Finally, we briefly discuss the introduction
of randomness in TVGs.Comment: A short version appeared in ADHOC-NOW'11. This version is to be
published in Internation Journal of Parallel, Emergent and Distributed
System
UNDERSTANDING COMMUNICATION NETWORK COHESIVENESS DURING ORGANIZATIONAL CRISIS: EFFECTS OF CLIQUE AND TRANSITIVITY
Various terms such as organizational mortality, organizational death, bankruptcy, decline, retrenchment and failure have been used in the literature to characterize different forms and facets of organizational crisis. Communication network studies have typically focused on nodes (individuals or organizations), relationships between those nodes, and subsequent affects of these relationships upon the network as a whole. Email networks in contemporary organizations are fairly representative of the underlying communications networks. We show that changes in communication networks and its associated group cohesiveness have implications for studying organizational crisis. In this paper, we analyze the changing communication network structure at Enron Corporation during the period of its crisis (2000-2001). Our goal was to understand how communication patterns and structure were affected by organizational crisis. Drawing on communication network crisis and group cohesiveness theory, we tested several propositions using the Enron email corpus: (1) Number of cliques increases, and (2) Communication network becomes increasingly transitive as organizations experience crisis. The results of the tests and their implications are discussed in this paper
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