In the paper we show that the bibliographic data can be transformed into a collection of compatible networks. Using network multiplication different interesting derived networks can be obtained. In defining them an appropriate normalization should be considered. The proposed approach can be applied also to other collections of compatible networks. The networks obtained from the bibliographic data bases can be large (hundreds of thousands of vertices). Fortunately they are sparse and can be still processed relatively fast. We answer the question when the multiplication of sparse networks preserves sparseness. The proposed approaches are illustrated with analyses of collection of networks on the topic "social network" obtained from the Web of Science. The works with large number of co-authors add large complete subgraphs to standard collaboration network thus bluring the collaboration structure. We show that using an appropriate normalization their effect can be neutralized. Among other, we propose a measure of collaborativness of authors with respect to a given bibliography and show how to compute the network of citations between authors and identify citation communities.
KeywordsCo-authorship Collaboration Two-mode network Network multiplication Sparse network Normalization
Mathematics Subject Classification (2000)91D30 62H30 68W40 93A15
The work was supported in part by the ARRS, Slovenia, grant P1-0294, as well as by grant within the EUROCORES Programme EUROGIGA (project GReGAS) of the European Science Foundation. The second author was financed in part by the European Union, European Social Fund.
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