By My T. Thai, Weili Wu, Hui Xiong
This publication offers fresh advancements at the theoretical, algorithmic, and alertness elements of massive information in advanced and Social Networks. The publication contains 4 elements, masking quite a lot of themes. the 1st a part of the ebook makes a speciality of info garage and information processing. It explores how the effective garage of information can essentially help in depth info entry and queries, which permits subtle research. It additionally appears to be like at how facts processing and visualization support to speak details in actual fact and successfully. the second one a part of the ebook is dedicated to the extraction of crucial details and the prediction of web pages. The e-book indicates how immense facts research can be utilized to appreciate the pursuits, situation, and seek background of clients and supply extra exact predictions of consumer habit. The latter elements of the publication conceal the security of privateness and safety, and emergent purposes of huge info and social networks. It analyzes how you can version rumor diffusion, determine incorrect information from great facts, and layout intervention techniques. purposes of massive facts and social networks in multilayer networks and multiparty platforms also are coated in-depth.
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Extra resources for Big data in complex and social networks
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . , Twitter) applications, and in response there is a growing need for analysis methods that can handle this terabyte-size input. To provide an effective and advanced data processing environment for various types of social data analysis such as political discourses, trending topics, evolution of user behavior, social bots detection and orchestrated campaigns, we need to support both query and complex analysis efficiently.
Finally, there are two existing applications for visualizing data in hyperbolic space, namely Hyperbolic Tree Viewer  and Hypertree . Although many other examples exist, they all suffer from different shortcomings, in particular problems regarding the inclusion of additional data dimensions, and the absence of a means to guide the user to those regions of the data that might be called “interesting”, calling for novel approaches. 9 CONCLUSIONS In this chapter, we developed a big data analytics (BDA) and exploitation framework for complex and social networks leveraging significant properties of hyperbolic geometry in this field.
Hyperbolic Big Data Analytics within Complex and Social Networks 35 31. J. Kleinberg, “The Small-World Phenomenon: an Algorithmic Perspective”, In Proc. of the 32 Annual ACM Symposium on Theory of Computing (STOC ’00), New York, NY, USA, pp. 163-170, 2000. 32. E. Stai, J. S. Baras, S. Papavassiliou, “Social Networks over Wireless Networks”, in Proc. of the 51st IEEE Conf. on Decision and Control (CDC), Hawaii, Dec. 2012. 33. E. Stai, S. Papavassiliou, J. S. 2360942, October 2014. 34. E. Stai, S.