Optimization Problems In Social Networks

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Handbook of Optimization in Complex Networks

Author : My T. Thai
Publisher : Springer Science & Business Media
ISBN 13 : 1461408571
Total Pages : 539 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Handbook of Optimization in Complex Networks by : My T. Thai

Download or read book Handbook of Optimization in Complex Networks written by My T. Thai and published by Springer Science & Business Media. This book was released on 2011-11-25 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimization Problems in Social Networks

Author : Guangmo Tong
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (15 download)

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Book Synopsis Optimization Problems in Social Networks by : Guangmo Tong

Download or read book Optimization Problems in Social Networks written by Guangmo Tong and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Influence Optimization Problems in Social Networks

Author : Shuyang Gu
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis Influence Optimization Problems in Social Networks by : Shuyang Gu

Download or read book Influence Optimization Problems in Social Networks written by Shuyang Gu and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modeling and Optimization for Mobile Social Networks

Author : Zhou Su
Publisher : Springer
ISBN 13 : 3319479229
Total Pages : 128 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Modeling and Optimization for Mobile Social Networks by : Zhou Su

Download or read book Modeling and Optimization for Mobile Social Networks written by Zhou Su and published by Springer. This book was released on 2016-11-25 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimal Social Influence

Author : Wen Xu
Publisher : Springer Nature
ISBN 13 : 303037775X
Total Pages : 129 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Optimal Social Influence by : Wen Xu

Download or read book Optimal Social Influence written by Wen Xu and published by Springer Nature. This book was released on 2020-01-29 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Optimization in Complex Networks

Author : My T. Thai
Publisher : Springer Science & Business Media
ISBN 13 : 1461407540
Total Pages : 546 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Handbook of Optimization in Complex Networks by : My T. Thai

Download or read book Handbook of Optimization in Complex Networks written by My T. Thai and published by Springer Science & Business Media. This book was released on 2012-01-28 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Optimization in Complex Networks

Author : My T. Thai
Publisher : Springer
ISBN 13 : 9781489999559
Total Pages : 546 pages
Book Rating : 4.9/5 (995 download)

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Book Synopsis Handbook of Optimization in Complex Networks by : My T. Thai

Download or read book Handbook of Optimization in Complex Networks written by My T. Thai and published by Springer. This book was released on 2014-03-03 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Network Optimization Problems: Algorithms, Applications And Complexity

Author : Ding-zhu Du
Publisher : World Scientific
ISBN 13 : 9814504580
Total Pages : 417 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Network Optimization Problems: Algorithms, Applications And Complexity by : Ding-zhu Du

Download or read book Network Optimization Problems: Algorithms, Applications And Complexity written by Ding-zhu Du and published by World Scientific. This book was released on 1993-04-27 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Optimization Problems for Maximizing Influence in Social Networks

Author : Smita Ghosh
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis Optimization Problems for Maximizing Influence in Social Networks by : Smita Ghosh

Download or read book Optimization Problems for Maximizing Influence in Social Networks written by Smita Ghosh and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimization in Social Networks

Author : Yuqing Zhu
Publisher :
ISBN 13 :
Total Pages : 204 pages
Book Rating : 4.:/5 (913 download)

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Book Synopsis Optimization in Social Networks by : Yuqing Zhu

Download or read book Optimization in Social Networks written by Yuqing Zhu and published by . This book was released on 2014 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Storage for Social Networks

Author : Duc A. Tran
Publisher : Springer Science & Business Media
ISBN 13 : 1461446368
Total Pages : 53 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Data Storage for Social Networks by : Duc A. Tran

Download or read book Data Storage for Social Networks written by Duc A. Tran and published by Springer Science & Business Media. This book was released on 2012-08-15 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step to address scalability. The next step is to determine how best to store the data across multiple servers. This problem has been widely-studied in the literature of distributed and database systems. OSNs, however, represent a different class of data systems. When a user spends time on a social network, the data mostly requested is her own and that of her friends; e.g., in Facebook or Twitter, these data are the status updates posted by herself as well as that posted by the friends. This so-called social locality should be taken into account when determining the server locations to store these data, so that when a user issues a read request, all its relevant data can be returned quickly and efficiently. Social locality is not a design factor in traditional storage systems where data requests are always processed independently. Even for today’s OSNs, social locality is not yet considered in their data partition schemes. These schemes rely on distributed hash tables (DHT), using consistent hashing to assign the users’ data to the servers. The random nature of DHT leads to weak social locality which has been shown to result in poor performance under heavy request loads. Data Storage for Social Networks: A Socially Aware Approach is aimed at reviewing the current literature of data storage for online social networks and discussing new methods that take into account social awareness in designing efficient data storage.

COMMUNITY DETECTION FOR SOCIAL NETWORK ANALYSIS

Author : Seema Rani
Publisher :
ISBN 13 :
Total Pages : 132 pages
Book Rating : 4.2/5 (1 download)

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Book Synopsis COMMUNITY DETECTION FOR SOCIAL NETWORK ANALYSIS by : Seema Rani

Download or read book COMMUNITY DETECTION FOR SOCIAL NETWORK ANALYSIS written by Seema Rani and published by . This book was released on 2022-02-20 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Evolving Heterogeneous and Subcultured Social Networks for Optimization Problem Solving in Cultural Algorithms

Author : Yousof Gawasmeh
Publisher :
ISBN 13 :
Total Pages : 133 pages
Book Rating : 4.:/5 (944 download)

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Book Synopsis Evolving Heterogeneous and Subcultured Social Networks for Optimization Problem Solving in Cultural Algorithms by : Yousof Gawasmeh

Download or read book Evolving Heterogeneous and Subcultured Social Networks for Optimization Problem Solving in Cultural Algorithms written by Yousof Gawasmeh and published by . This book was released on 2015 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: We show that heterogeneous approaches begin to dominate homogeneous ones as the problem complexity increases. A second heterogeneous approach, sub-culutres, will be introduced by dividing the social fabric into smaller networks. The three different social fabrics (homogeneous, heterogeneous and Sub-Cultures) were then compared relative to a variety of benchmark landscapes of varying entropy, from static to chaotic. We show that as the number of independent processes that are involved in the production of a landscape increases, the more advantageous subcultures are in directing the population to a solution. We will support our results with t-test statistics and social fabric metrics performance analysis.

Content Spread and User Relations in Social Computing

Author : Yi Li
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (114 download)

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Book Synopsis Content Spread and User Relations in Social Computing by : Yi Li

Download or read book Content Spread and User Relations in Social Computing written by Yi Li and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid growth of social media and the rise in popularity of social networks, content sharing and spreading have become the major activities for social media users. One of the valuable characteristics of social networks is its capability for user generated content to circulate rapidly through the whole network and spread influence on others. Another characteristic is its openness to everyone. It enables not only news organizations and government agencies to post information, but also ordinary citizens to post from their own perspectives and experiences. In this way, users have the access to more comprehensive and complicated information online. On one hand, social networks offer users many valuable experiences. We can take advantages of social networks such that, for example, the spread of innovation ideas can be maximized, or the expectation of users can be satisfied. On the other hand, we hope to take actions on the negative side that social networks bring to users. For example, to limit the spread of rumors and misinformation or to minimize the negative influence of cybervictims. In this dissertation, we study several problems regarding both positive and negative content spread on social network. First, we study the emerging problems of misinformation/rumor blocking and minimizing the cyberbullying influence on specific user based on Independent Cascade diffusion model and its variance Competitive Independent Cascade model. We formulate these two problems as optimization problems and design algorithms with performance guarantees. Second, we propose a content spread maximization problem and formulate the problem from a marginal gain perspective. As the considered problems are all NP-hard, we focus on the analysis of approximation results. Third, because the network structures are changing dynamically, we predict the missing links and emerging links based on community structure. Last, we study the correlations between user generated content and their roles in online discussion forum.

Study in Big Data Harnessing and Related Problems

Author : Rong Jin
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Study in Big Data Harnessing and Related Problems by : Rong Jin

Download or read book Study in Big Data Harnessing and Related Problems written by Rong Jin and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social networks, such as Facebook and Twitter, have provided incredible opportunities for social communication between web users around the world. Social network analysis is an important problem in data harnessing. The analysis of social networks helps summarizing the interests and opinions of users (nodes), discovering patterns from the interactions (edges) between users, and mining the events that take place in online platforms. The information obtained by analyzing social networks could be especially valuable for many applications. Some typical examples include online advertisement targeting, viral marketing, personalized recommendation, health social media, social influence analysis, and citation network analysis. In this dissertation, we study two types of applications emerging from modern online social platforms in the view of social influence. One is influence maximization(IM) problem from a discount-based online viral marketing scenario, which aims at maximizing influence in the adoption of target products, and the other is online rumor source detection problem, in which the spread of misinformation is supposed to be minimized and the source is expected to be detected. We formulate them as set function optimization problems and design solutions with performance guarantees. In study of set function optimization, there is a challenge coming from the submodularity of objective function. That is, some of the practical problems are not submodular or supermodular, the existing greedy strategy cannot be directly applied to problems to get a guaranteed approximate solution. To solve those non-submodular and non-supermodular problems, one method called DS decomposition has been considered, in which given a set function, we decompose it to be representable as a difference between submodular functions. Based on this method, we further study a problem about how to find a DS decomposition efficiently and effectively. Then we propose a generalized framework that is made up of our novel algorithms under deterministic version and random version respectively to solve maximization of DS decomposition and show their performances under various combinatorial settings. In addition, we discuss our findings on the role of black-box, that has been an important component in study of computational complexity theory as well as has been used for establishing the hardness of problems, about its implied power and limitations in study of data-driven computation for proving solutions to some computational problems.

Optimization Problems in Graph Theory

Author : Boris Goldengorin
Publisher : Springer
ISBN 13 : 331994830X
Total Pages : 341 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Optimization Problems in Graph Theory by : Boris Goldengorin

Download or read book Optimization Problems in Graph Theory written by Boris Goldengorin and published by Springer. This book was released on 2018-09-27 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin’s fundamental contributions to advanced methods and techniques in combinatorial optimization. Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. Topics covered in this work include: · Algorithmic aspects of problems with disjoint cycles in graphs · Graphs where maximal cliques and stable sets intersect · The maximum independent set problem with special classes · A general technique for heuristic algorithms for optimization problems · The network design problem with cut constraints · Algorithms for computing the frustration index of a signed graph · A heuristic approach for studying the patrol problem on a graph · Minimum possible sum and product of the proper connection number · Structural and algorithmic results on branchings in digraphs · Improved upper bounds for Korkel--Ghosh benchmark SPLP instances

Open Problems in Optimization and Data Analysis

Author : Panos M. Pardalos
Publisher : Springer
ISBN 13 : 3319991426
Total Pages : 330 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Open Problems in Optimization and Data Analysis by : Panos M. Pardalos

Download or read book Open Problems in Optimization and Data Analysis written by Panos M. Pardalos and published by Springer. This book was released on 2018-12-04 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.