Learning from Multiple Social Networks PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Learning from Multiple Social Networks PDF full book. Access full book title Learning from Multiple Social Networks by Liqiang Nie. Download full books in PDF and EPUB format.
Author: Liqiang Nie
Publisher: Springer Nature
ISBN: 3031023005
Category : Computers
Languages : en
Pages : 102
Get Book Here
Book Description
With the proliferation of social network services, more and more social users, such as individuals and organizations, are simultaneously involved in multiple social networks for various purposes. In fact, multiple social networks characterize the same social users from different perspectives, and their contexts are usually consistent or complementary rather than independent. Hence, as compared to using information from a single social network, appropriate aggregation of multiple social networks offers us a better way to comprehensively understand the given social users. Learning across multiple social networks brings opportunities to new services and applications as well as new insights on user online behaviors, yet it raises tough challenges: (1) How can we map different social network accounts to the same social users? (2) How can we complete the item-wise and block-wise missing data? (3) How can we leverage the relatedness among sources to strengthen the learning performance? And (4) How can we jointly model the dual-heterogeneities: multiple tasks exist for the given application and each task has various features from multiple sources? These questions have been largely unexplored to date. We noticed this timely opportunity, and in this book we present some state-of-the-art theories and novel practical applications on aggregation of multiple social networks. In particular, we first introduce multi-source dataset construction. We then introduce how to effectively and efficiently complete the item-wise and block-wise missing data, which are caused by the inactive social users in some social networks. We next detail the proposed multi-source mono-task learning model and its application in volunteerism tendency prediction. As a counterpart, we also present a mono-source multi-task learning model and apply it to user interest inference. We seamlessly unify these models with the so-called multi-source multi-task learning, and demonstrate several application scenarios, such as occupation prediction. Finally, we conclude the book and figure out the future research directions in multiple social network learning, including the privacy issues and source complementarity modeling. This is preliminary research on learning from multiple social networks, and we hope it can inspire more active researchers to work on this exciting area. If we have seen further it is by standing on the shoulders of giants.
Author: Liqiang Nie
Publisher: Springer Nature
ISBN: 3031023005
Category : Computers
Languages : en
Pages : 102
Get Book Here
Book Description
With the proliferation of social network services, more and more social users, such as individuals and organizations, are simultaneously involved in multiple social networks for various purposes. In fact, multiple social networks characterize the same social users from different perspectives, and their contexts are usually consistent or complementary rather than independent. Hence, as compared to using information from a single social network, appropriate aggregation of multiple social networks offers us a better way to comprehensively understand the given social users. Learning across multiple social networks brings opportunities to new services and applications as well as new insights on user online behaviors, yet it raises tough challenges: (1) How can we map different social network accounts to the same social users? (2) How can we complete the item-wise and block-wise missing data? (3) How can we leverage the relatedness among sources to strengthen the learning performance? And (4) How can we jointly model the dual-heterogeneities: multiple tasks exist for the given application and each task has various features from multiple sources? These questions have been largely unexplored to date. We noticed this timely opportunity, and in this book we present some state-of-the-art theories and novel practical applications on aggregation of multiple social networks. In particular, we first introduce multi-source dataset construction. We then introduce how to effectively and efficiently complete the item-wise and block-wise missing data, which are caused by the inactive social users in some social networks. We next detail the proposed multi-source mono-task learning model and its application in volunteerism tendency prediction. As a counterpart, we also present a mono-source multi-task learning model and apply it to user interest inference. We seamlessly unify these models with the so-called multi-source multi-task learning, and demonstrate several application scenarios, such as occupation prediction. Finally, we conclude the book and figure out the future research directions in multiple social network learning, including the privacy issues and source complementarity modeling. This is preliminary research on learning from multiple social networks, and we hope it can inspire more active researchers to work on this exciting area. If we have seen further it is by standing on the shoulders of giants.
Author: Yann Bramoullé
Publisher: Oxford University Press
ISBN: 0190216832
Category : Business & Economics
Languages : en
Pages : 857
Get Book Here
Book Description
The Oxford Handbook of the Economics of Networks represents the frontier of research into how and why networks they form, how they influence behavior, how they help govern outcomes in an interactive world, and how they shape collective decision making, opinion formation, and diffusion dynamics. From a methodological perspective, the contributors to this volume devote attention to theory, field experiments, laboratory experiments, and econometrics. Theoretical work in network formation, games played on networks, repeated games, and the interaction between linking and behavior is synthesized. A number of chapters are devoted to studying social process mediated by networks. Topics here include opinion formation, diffusion of information and disease, and learning. There are also chapters devoted to financial contagion and systemic risk, motivated in part by the recent financial crises. Another section discusses communities, with applications including social trust, favor exchange, and social collateral; the importance of communities for migration patterns; and the role that networks and communities play in the labor market. A prominent role of networks, from an economic perspective, is that they mediate trade. Several chapters cover bilateral trade in networks, strategic intermediation, and the role of networks in international trade. Contributions discuss as well the role of networks for organizations. On the one hand, one chapter discusses the role of networks for the performance of organizations, while two other chapters discuss managing networks of consumers and pricing in the presence of network-based spillovers. Finally, the authors discuss the internet as a network with attention to the issue of net neutrality.
Author: Alain Degenne
Publisher: SAGE
ISBN: 1847876846
Category : Social Science
Languages : en
Pages : 257
Get Book Here
Book Description
This first-rate introduction to the study of social networks combines a hands-on manual with an up-to-date review of the latest research and techniques. The authors provide a thorough grounding in the application of the methods of social network analysis. They offer an understanding of the theory of social structures in which social network analysis is grounded, a summary of the concepts needed for dealing with more advanced techniques, and guides for using the primary computer software packages for social network analysis.
Author: Suraj Bandyopadhyay
Publisher: SAGE Publications
ISBN: 1483305376
Category : Social Science
Languages : en
Pages : 250
Get Book Here
Book Description
Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze network data. Clearly demonstrates how graph-theoretic and statistical techniques can be employed to study some important parameters of global social networks. The authors uses real life village-level social networks to illustrate the practicalities, potentials, and constraints of social network analysis ("SNA"). They also offer relevant sampling and inferential aspects of the techniques while dealing with potentially large networks. Intended Audience This supplemental text is ideal for a variety of graduate and doctoral level courses in social network analysis in the social, behavioral, and health sciences
Author: Bebo White
Publisher: Springer Science & Business Media
ISBN: 3642203914
Category : Education
Languages : en
Pages : 438
Get Book Here
Book Description
Online social media have transformed the face of human interaction in the 21st century. Wikis, blogs, online groups and forums, podcasts, virtual worlds, and social tagging are but a few of the applications enabling innovative behaviors that support acquisition, access, manipulation, retrieval, and visualization of information. It is, therefore, no surprise that educational practitioners and theorists have begun to explore how social media can be harnessed to describe and implement new paradigms for communication, learning, and education. The editors’ goal in publishing this book was to identify original research on the application of online social media and related technologies in education as well as emerging applications in Web technologies that could provide and shape future educational platforms. The selected contributions deal with questions such as how social media can truly enrich and enhance learning and teaching experiences in ways not otherwise possible; how learning can be integrated in a distributed and ubiquitous social computing environment; or what theories, paradigms, and models are applicable for the support of social computing in education. Researchers in education or educational software will find interesting and sometimes provocative chapters on paradigms and methodologies, virtual and mobile learning spaces, and assessment and social factors. Practitioners in these fields will benefit from an additional section devoted to case studies and first experience reports.
Author: Mark E. Dickison
Publisher: Cambridge University Press
ISBN: 1107079497
Category : Computers
Languages : en
Pages : 215
Get Book Here
Book Description
This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1466686154
Category : Social Science
Languages : en
Pages : 2337
Get Book Here
Book Description
In the digital era, users from around the world are constantly connected over a global network, where they have the ability to connect, share, and collaborate like never before. To make the most of this new environment, researchers and software developers must understand users’ needs and expectations. Social Media and Networking: Concepts, Methodologies, Tools, and Applications explores the burgeoning global community made possible by Web 2.0 technologies and a universal, interconnected society. With four volumes of chapters related to digital media, online engagement, and virtual environments, this multi-volume reference is an essential source for software developers, web designers, researchers, students, and IT specialists interested in the growing field of digital media and engagement. This four-volume reference includes various chapters covering topics related to Web 2.0, e-governance, social media activism, internet privacy, digital and virtual communities, e-business, customer relationship management, and more.
Author: Brian V. Carolan
Publisher: SAGE Publications
ISBN: 1483303519
Category : Social Science
Languages : en
Pages : 345
Get Book Here
Book Description
Social Network Analysis and Education: Theory, Methods & Applications provides an introduction to the theories, methods, and applications that constitute the social network perspective. Unlike more general texts, this applied title is designed for those current and aspiring educational researchers learning how to study, conceptualize, and analyze social networks. Brian V. Carolan's main intent is to encourage you to consider the social network perspective in light of your emerging research interests and evaluate how well this perspective illuminates the social complexities surrounding educational phenomena. Relying on diverse examples drawn from the educational research literature, this book makes explicit how the theories and methods associated with social network analysis can be used to better describe and explain the social complexities surrounding varied educational phenomena.
Author: Quan Zheng
Publisher: CRC Press
ISBN: 1315390604
Category : Computers
Languages : en
Pages : 339
Get Book Here
Book Description
Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from a range of realistic possibilities, including different types of relationships, different strengths in the directions of a pair, positive and negative relationships, and relationships whose intensities change with time. For each possibility, the book shows how to model the social network using spectral embedding. It also shows how to compose the techniques so that multiple edge semantics can be modeled together, and the modeling techniques are then applied to a range of datasets. Features Introduces the reader to difficulties with current social network analysis, and the need for richer representations of relationships among nodes, including accounting for intensity, direction, type, positive/negative, and changing intensities over time Presents a novel mechanism to allow social networks with qualitatively different kinds of relationships to be described and analyzed Includes extensions to the important technique of spectral embedding, shows that they are mathematically well motivated and proves that their results are appropriate Shows how to exploit embeddings to understand structures within social networks, including subgroups, positional significance, link or edge prediction, consistency of role in different contexts, and net flow of properties through a node Illustrates the use of the approach for real-world problems for online social networks, criminal and drug smuggling networks, and networks where the nodes are themselves groups Suitable for researchers and students in social network research, data science, statistical learning, and related areas, this book will help to provide a deeper understanding of real-world social networks.
Author: My T. Thai
Publisher: CRC Press
ISBN: 1315396696
Category : Business & Economics
Languages : en
Pages : 253
Get Book Here
Book Description
This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.
