By Mrutyunjaya Panda, Satchidananda Dehuri, Gi-Nam Wang

ISBN-10: 3319051636

ISBN-13: 9783319051635

ISBN-10: 3319051644

ISBN-13: 9783319051642

With the proliferation of social media and online groups in networked international a wide gamut of knowledge has been accrued and kept in databases. the speed at which such information is saved is transforming into at a gorgeous expense and pushing the classical equipment of knowledge research to their limits. This ebook offers an built-in framework of modern empirical and theoretical learn on social community research in keeping with a variety of ideas from a number of disciplines like facts mining, social sciences, arithmetic, information, physics, community technological know-how, computing device studying with visualization strategies and protection. The e-book illustrates the possibility of multi-disciplinary innovations in numerous actual existence difficulties and intends to encourage researchers in social community research to layout better instruments through integrating swarm intelligence and knowledge mining.

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Extra resources for Social Networking: Mining, Visualization, and Security

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American Economic Review 97, 92–98 (2007) 33. com/publications/article/123503/ 34. : Impact of social network structure on content propagation: A study using youtube data. Quantitative Marketing and Economics 10(1), 111–150 (2012) 35. : Power and centrality: A family of measures. American Journal of Sociology 92(5), 1170–1182 (1987) 36. : The centrality index of a graph. Psychometrika 31(4), 581–603 (1966) 37. : Theoretical foundations for centrality measures. American Journal of Sociology 96(6), 1478–1504 (1991) Diffusion of Information in Social Networks 21 38.

American Journal of Sociology 113, 702–734 (2007) 30. : The strength of weak ties. The American Journal of Sociology 78(6), 1360–1380 (1973) 31. : Dynamical strength of social ties in information spreading. Phys. Rev. E 83, 045102 (2011) 32. : The diffusion of behavior and equilibrium properties in network games. American Economic Review 97, 92–98 (2007) 33. com/publications/article/123503/ 34. : Impact of social network structure on content propagation: A study using youtube data. Quantitative Marketing and Economics 10(1), 111–150 (2012) 35.

Two methods were discussed to identify the set of influencers, employing measures of network centrality. We then look at multiple sources of information and consider both the cases where the sources collaborate or compete with each other. Finally we look at the problem of locating the source of diffusion in a social networks. Both, techniques that assume full knowledge of the network and those that do not are presented. Several challenges still remain in this area of study including optimal placement of sensors in the networks to aid in zeroing in on the sources of diffusion, finding the source of diffusion when the diffusion graph is not completely known, etc.

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Social Networking: Mining, Visualization, and Security by Mrutyunjaya Panda, Satchidananda Dehuri, Gi-Nam Wang


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