[PDF] Optimization Problems In Social Networks eBook

Author : My T. Thai
Publisher : Springer Science & Business Media
Page : 539 pages
File Size : 21,2 MB
Release : 2011-11-25
Category : Mathematics
ISBN : 1461408571

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Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Author : Shuyang Gu
Publisher :
Page : pages
File Size : 19,19 MB
Release : 2020
Category : Influence (Psychology)
ISBN :

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Online social networks have been developing and prosperous during the last two decades, my dissertation focus on the study of social influence. Several practical problems about social influence are formulated as optimization problems. First, users of online social networks such as Twitter, Instagram have a nature of expanding social relationships. Thus, one important social network service is to provide potential friends to a user that he or she might be interested in, which is called friend recommendation. Different from friend recommendation, which is a passive way for an user to connect with a potential friend, in my work, I tackle a different problem named active friending as an optimization problem about how to friend a person in social networks taking advantage of social influence to increase the acceptance probability by maximizing mutual friends influence. Second, the influence maximization problem has been studied extensively with the development of online social networks. Most of the existing works focus on the maximization of influence spread under the assumption that the number of influenced users determines the success of product promotion. However, the profit of some products such as online game depends on the interactions among users besides the number of users. We take both the number of active users and the user-to-user interactions into account and propose the interaction-aware influence maximization problem. Furthermore, due to the uncertainty in edge probability estimates in social networks, we propose the robust profit maximization problem to have the best solution in the worst case of probability settings.

Author : Guangmo Tong
Publisher :
Page : pages
File Size : 32,50 MB
Release : 2018
Category : Information networks
ISBN :

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Social networks have become the dominant platform for daily communication, social activities and viral marketing. The past years have witnessed a drastic increase in the population of social network users. On one hand, we aim at fully taking the advantage of social networks such that, for example, the effect of the online advertising can be maximized or the expectation of the users can be satisfied. On the other hand, negative impact resulted by social networks should be constrained. For example, to limit the spread of misinformation or to protect the privacy of online users. In this dissertation, we study the problems emerging from modern online social systems, from the view of information diffusion. Based on different information diffusion models, we study several problems regarding viral marketing, online friending, rumor blocking, etc. We formulate the considered problems as optimization problems and design solutions with performance guarantees. As the considered problems are all NP-hard, we focus on the analysis of approximation result. Another challenge comes from the high scale of real social network and the #P-hard nature of computing information influence. In order to provide efficient algorithms with respect to running time, we adopt effective sampling techniques to improve the efficiency of the solutions.

Author : My T. Thai
Publisher : Springer
Page : 546 pages
File Size : 15,99 MB
Release : 2014-03-03
Category : Mathematics
ISBN : 9781489999559

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Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Author : My T. Thai
Publisher : Springer Science & Business Media
Page : 546 pages
File Size : 20,55 MB
Release : 2012-01-28
Category : Mathematics
ISBN : 1461407540

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Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Author : Wen Xu
Publisher : Springer Nature
Page : 129 pages
File Size : 27,8 MB
Release : 2020-01-29
Category : Mathematics
ISBN : 303037775X

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This self-contained book describes social influence from a computational point of view, with a focus on recent and practical applications, models, algorithms and open topics for future research. Researchers, scholars, postgraduates and developers interested in research on social networking and the social influence related issues will find this book useful and motivating. The latest research on social computing is presented along with and illustrations on how to understand and manipulate social influence for knowledge discovery by applying various data mining techniques in real world scenarios. Experimental reports, survey papers, models and algorithms with specific optimization problems are depicted. The main topics covered in this book are: chrematistics of social networks, modeling of social influence propagation, popular research problems in social influence analysis such as influence maximization, rumor blocking, rumor source detection, and multiple social influence competing.

Author : Zhou Su
Publisher : Springer
Page : 128 pages
File Size : 12,43 MB
Release : 2016-11-25
Category : Computers
ISBN : 3319479229

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This book investigates the modeling and optimization issues in mobile social networks (MSNs). Firstly, the architecture and applications of MSNs are examined. The existing works on MSNs are reviewed by specifying the critical challenges and research issues. Then, with the introduction of MSN-based social graph and information dissemination mechanisms, the analytical model for epidemic information dissemination with opportunistic Links in MSNs is discussed. In addition, optimal resource allocation is studied based on a heterogeneous architecture, which provides mobile social services with high capacity and low latency. Finally, this book summarize some open problems and future research directions in MSNs. Written for researchers and academics, this book is useful for anyone working on mobile networks, network architecture, or content delivery. It is also valuable for advanced-level students of computer science.

Author : Smita Ghosh
Publisher :
Page : 0 pages
File Size : 13,44 MB
Release : 2020
Category : Collective behavior
ISBN :

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Social Networks have become very popular in the past decade. They started as platforms to stay connected with friends and family living in different parts of the world, but have evolved into so much more, resulting in Social Network Analysis (SNA) becoming a very popular area of research. One popular problem under the umbrella of SNA is Influence Maximization (IM), which aims at selecting k initially influenced nodes (users) in a social network that will maximize the expected number of eventually-influenced nodes (users) in the network. Influence maximization finds its application in many domains, such as viral marketing, content maximization, epidemic control, virus eradication, rumor control and misinformation blocking. In this dissertation, we study various variations of the IM problem such as Composed Influence Maximization, Group Influence Maximization, Profit Maximization in Groups and Rumor Blocking Problem in Social Networks. We formulate objective functions for these problems and as most of them are NP-hard, we focus on finding methods that ensure efficient estimation of these functions. The two main challenges we face are submodularity and scalibility. To design efficient algorithms, we perform simulations with sampling techniques to improve the effectiveness of our solution approach.

Author : Ding-zhu Du
Publisher : World Scientific
Page : 417 pages
File Size : 45,3 MB
Release : 1993-04-27
Category :
ISBN : 9814504580

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In the past few decades, there has been a large amount of work on algorithms for linear network flow problems, special classes of network problems such as assignment problems (linear and quadratic), Steiner tree problem, topology network design and nonconvex cost network flow problems.Network optimization problems find numerous applications in transportation, in communication network design, in production and inventory planning, in facilities location and allocation, and in VLSI design.The purpose of this book is to cover a spectrum of recent developments in network optimization problems, from linear networks to general nonconvex network flow problems./a

Author : Yuqing Zhu
Publisher :
Page : 204 pages
File Size : 34,62 MB
Release : 2014
Category : Approximation algorithms
ISBN :

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Social networks have shown increasing popularity in real-world applications. In this dissertation, I study several optimization problems in social networks. In Chapter 1, I propose an approximation algorithm for influence maximization problem in social networks which works better than the start-of-arts under certain circumstances. In Chapter 2, noticing that for a company, the profit and influence are often different, I propose the balanced influence and profit (BIP) problem and design effective algorithms. In Chapter 3, I propose a new influence diffusion model - Timeliness Independent Cascade (TIC) for the case where multiple companies spread their influence and compete each other in a social network. I present the FairInf problem aiming at giving different companies fair influence spreads under TIC model. Several algorithms are designed for FairInf problem. In Chapter 4, a new partitioning method for social networks has been devised. This method is based on the mutual relationship between each pair of individuals in the social network, and works better than existing partitioning strategy on real world datasets.