Finding Statistically Significant Communities in Networks
نویسندگان
چکیده
منابع مشابه
Finding Statistically Significant Communities in Networks
Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we pres...
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The assessment of a cluster’s significance given the null (configuration) model relies on the estimation of the probability described in Eq. 1 of the main text. This function has to be evaluated many times along the execution of OSLOM in order to clean up each cluster and to evaluate the clusters at the different hierarchical levels. We explain here how the values of the distribution function c...
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Various networks exist in the world today including biological, social, information, and communication networks with the Internet as the largest network of all. One salient structural feature of these networks is the formation of groups or communities of vertices that tend to be more connected to each other within the same group than to those outside. Therefore, the detection of these communiti...
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In the questionnaire analysis, finding whether there is a statistically significant difference between two or more groups in a continuous measure is one of the major problems in researches. However, it is difficult for researchers to solve the issue of finding possible statistically significant difference, namely “Statistically Significant Difference Unawareness Issue”. There are two causes to ...
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ژورنال
عنوان ژورنال: PLoS ONE
سال: 2011
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0018961