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.

Download or read book Big Data in Complex and Social Networks written by My T. Thai and published by CRC Press. This book was released on 2016-12-01 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Securecsocial Secure Cloud based Social Network written by Atrey Pradeep and published by World Scientific. This book was released on 2019-08-19 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of online social networks (OSNs) has grown exponentially in recent years, and these OSNs continue to have an ever-increasing impact on human lives. There are many concerns regarding the privacy of users in these environments, such as how trustworthy the social network operators (SNOs) are.This book presents a way to tackle the security and privacy issues in current OSNs through a new framework for online social networking, based on distributed cloud-based datacenters (CDCs) and using Shamir's secret sharing (SSS) as the method of encrypting user profile data. The framework aims to fulfill two contradictory goals: maintaining the utility of an OSN and preserving privacy of its users. The key feature of the framework lies in relinquishing control of a central authority over user's data (which is what usually happens in the current OSNs, e.g. Facebook keeps all our data) and distributing it to multiple CDCs in encrypted form. The use of SSS ensures perfect security, which means that the security of data does not rely on any unproven computational assumptions.In this unique book, SNOs are considered as an adversary instead of external adversary. This paves the way for researchers to think beyond the privacy setting mechanism within an OSN to protect users' data.

Download or read book Big Data Analytics written by Mrutyunjaya Panda and published by CRC Press. This book was released on 2018-12-12 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

Download or read book Analyzing and Securing Social Networks written by Bhavani Thuraisingham and published by CRC Press. This book was released on 2016-04-06 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technolo

Download or read book Social Media Data Mining and Analytics written by Gabor Szabo and published by John Wiley & Sons. This book was released on 2018-09-19 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

Download or read book NoSQL Databases as Social Networks Storage Systems written by Dražena Gašpar and published by . This book was released on 2018 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper presents analysis of the storage systems used by social network sites. Namely, the social networks are one of the main driving forces behind the NoSQL database development. Facebook and Twitter were, together with other the Big Data players like Google and Amazon, first faced with the limitations of relational databases in solving their needs related to unprecedented transaction volumes, expectations of low-latency access to massive datasets, and nearly perfect service availability while operating in an unreliable environment. The first NoSQL databases arose as internal solutions created out of necessity, and not with the intention to abandon relational databases. But the main question is if, after more than ten years of development, NoSQL databases proved that they could be valuable storage solutions for social networks' data. The paper shows that there is still a lot of room for improvement in the use of NoSQL in social networks and provides some suggestions on how NoSQL databases can bring additional value to social network sites.

Download or read book Big Data in Complex and Social Networks written by My T. Thai and published by CRC Press. This book was released on 2016-12-01 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Social Network Data Analytics written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2011-03-18 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

Download or read book Computational Social Networks written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2012-08-14 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the second of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, concentrating on topics relating to security and privacy (the other two volumes review Tools, Perspectives, and Applications, and Mining and Visualization in CSNs). Topics and features: presents the latest advances in security and privacy issues in CSNs, and illustrates how both organizations and individuals can be protected from real-world threats; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, with a focus on issues of security, privacy, and anonymization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.

Download or read book Security and Privacy in Social Networks and Big Data written by Xiaofeng Chen and published by Springer Nature. This book was released on 2022-10-09 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 8th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2022, which took place in Xi'an, China, in October 2022. The 23 papers presented in this volume were carefully reviewed and selected from 103 submissions. The papers were evaluated on the basis of their significance, novelty, technical quality, as well as on their practical impact or their level of advancement of the field’s foundations. They were organized in topical sections as follows: Cryptography and its applications; Network security and privacy protection; Data detection; Blockchain and its applications.

Download or read book Security Designs for the Cloud IoT and Social Networking written by Dac-Nhuong Le and published by John Wiley & Sons. This book was released on 2019-11-05 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Security concerns around the rapid growth and variety of devices that are controlled and managed over the Internet is an immediate potential threat to all who own or use them. This book examines the issues surrounding these problems, vulnerabilities, what can be done to solve the problems, investigating the roots of the problems and how programming and attention to good security practice can combat the threats today that are a result of lax security processes on the Internet of Things, cloud computing and social media.

Download or read book Exploratory Social Network Analysis with Pajek written by Wouter de Nooy and published by Cambridge University Press. This book was released on 2011-09-30 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: An extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software and data sets are available so readers can learn network analysis through application and case studies. Readers will have the knowledge, skill and tools to apply social network analysis across the social sciences, from anthropology and sociology to business administration and history. This second edition has a new chapter on random network models, for example, scale-free and small-world networks and Monte Carlo simulation; discussion of multiple relations, islands and matrix multiplication; new structural indices such as eigenvector centrality, degree distribution and clustering coefficients; new visualization options that include circular layout for partitions and drawing a network geographically as a 3D surface; and using Unicode labels.

Download or read book Machine Learning Techniques for Online Social Networks written by Tansel Özyer and published by Springer. This book was released on 2018-05-30 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields.

Download or read book Principles of Social Networking written by Anupam Biswas and published by Springer Nature. This book was released on 2021-08-18 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new and innovative current discoveries in social networking which contribute enough knowledge to the research community. The book includes chapters presenting research advances in social network analysis and issues emerged with diverse social media data. The book also presents applications of the theoretical algorithms and network models to analyze real-world large-scale social networks and the data emanating from them as well as characterize the topology and behavior of these networks. Furthermore, the book covers extremely debated topics, surveys, future trends, issues, and challenges.

Download or read book Social Networks and Health written by Thomas W. Valente and published by Oxford University Press. This book was released on 2010-03-25 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Relationships and the pattern of relationships have a large and varied influence on both individual and group action. The fundamental distinction of social network analysis research is that relationships are of paramount importance in explaining behavior. Because of this, social network analysis offers many exciting tools and techniques for research and practice in a wide variety of medical and public health situations including organizational improvements, understanding risk behaviors, coordinating coalitions, and the delivery of health care services.This book provides an introduction to the major theories, methods, models, and findings of social network analysis research and application. In three sections, it presents a comprehensive overview of the topic; first in a survey of its historical and theoretical foundations, then in practical descriptions of the variety of methods currently in use, and finally in a discussion of its specific applications for behavior change in a public health context. Throughout, the text has been kept clear, concise, and comprehensible, with short mathematical formulas for some key indicators or concepts. Researchers and students alike will find it an invaluable resource for understanding and implementing social network analysis in their own practice.

Download or read book Social Network Analysis written by Xiaoming Fu and published by CRC Press. This book was released on 2017-03-31 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book addresses the issue of interdisciplinary understanding of collaboration on the topic of social network studies. Researchers and practitioners from various disciplines including sociology, computer science, socio-psychology, public health, complex systems, and management science have worked largely independently, each with quite different principles, terminologies, theories. and methodologies. The book aims to fill the gap among these disciplines with a number of the latest interdisciplinary collaboration studies.