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Titlebook: Computational Social Networks; Mining and Visualiza Ajith Abraham Book 2012 Springer-Verlag London 2012 Ad Hoc Network Applications and Ser

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https://doi.org/10.1007/978-3-319-27905-3ology based on the framework of business intelligence platform to support dynamic network modeling, analysis and data mining. Finally, China’s case study described the process of dynamic group-buying network modeling and analysis, as well as the results of the buyer behavior pattern analysis and min
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J. Stötter,H. Weck-Hannemann,E. Veulliettive measures while different types are not directly comparable to each other. Further, our analysis shows that narrowness of a Research Network’s subject area can be predicted using the connectedness of semantic similarity networks. Finally, conclusions are drawn and implications for future researc
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‘Sustainable Ageing’ in a World of Crisesesent our long-term research effort in analyzing Facebook, the largest and arguably most successful OSN today: it gathers more than 500 million users. Access to data about Facebook users and their friendship relations is restricted; thus, we acquired the necessary information directly from the front
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https://doi.org/10.1007/978-3-031-41594-4 data localization in a separate position; and centralized data in a single position approve that the concentration of data to one node. These behaviors are driven by complexity of the dataset and network nodes structure of the chosen log dataset.
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s; describes simulations of social networks, and the representation and analysis of social networks, highlighting methods for the data mining of CSNs; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.978-1-4471-6237-7978-1-4471-4054-2
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