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• W907125622 abstract "Large-scale computational generation and motif distribution analysis for the synthetic topology classes. We obtain a distinct motif pattern for each such class.Comprehensive motif analysis of online social networks (Facebook, Twitter, Google Plus) from which we obtain three quantifiable characteristic motif fingerprints.Mapping and similarity assessment of empirical networks onto topology classes, and defining a general methodology for such an approach.Correlation and discussion of the individual motifs that occur in each fingerprint, and an outlining of the functional properties behind the three online social platforms. Complex networks facilitate the understanding of natural and man-made processes and are classified based on the concepts they model: biological, technological, social or semantic. The relevant subgraphs in these networks, called network motifs, are demonstrated to show core aspects of network functionality and can be used to analyze complex networks based on their topological fingerprint. We propose a novel approach of classifying social networks based on their topological aspects using motifs. As such, we define the classifiers for regular, random, small-world and scale-free topologies, and then apply this classification on empirical networks. We then show how our study brings a new perspective on differentiating between online social networks like Facebook, Twitter and Google Plus based on the distribution of network motifs over the fundamental topology classes. Characteristic patterns of motifs are obtained for each of the analyzed online networks and are used to better explain the functional properties behind how people interact online and to define classifiers capable of mapping any online network to a set of topological-communicational properties." @default.
• W907125622 created "2016-06-24" @default.
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• W907125622 date "2016-01-01" @default.
• W907125622 modified "2023-10-04" @default.
• W907125622 title "Uncovering the fingerprint of online social networks using a network motif based approach" @default.
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• W907125622 doi "https://doi.org/10.1016/j.comcom.2015.07.002" @default.
• W907125622 hasPublicationYear "2016" @default.
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