Data Storage for Social Networks
Data Storage for Social Networks

Author: Duc A. Tran

Publisher: Springer Science & Business Media

Published: 2012-08-15

Total Pages: 53

ISBN-13: 1461446368

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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.

Big Data in Complex and Social Networks
Big Data in Complex and Social Networks

Author: My T. Thai

Publisher: CRC Press

Published: 2016-12-01

Total Pages: 253

ISBN-13: 1315396696

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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.

Securecsocial: Secure Cloud-based Social Network
Securecsocial: Secure Cloud-based Social Network

Author: Atrey Pradeep

Publisher: World Scientific

Published: 2019-08-19

Total Pages: 160

ISBN-13: 9811205930

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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.

Big Data Analytics
Big Data Analytics

Author: Mrutyunjaya Panda

Publisher: CRC Press

Published: 2018-12-12

Total Pages: 255

ISBN-13: 1351622587

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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.

Analyzing and Securing Social Networks
Analyzing and Securing Social Networks

Author: Bhavani Thuraisingham

Publisher: CRC Press

Published: 2016-04-06

Total Pages: 586

ISBN-13: 1482243288

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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

NoSQL Databases as Social Networks Storage Systems
NoSQL Databases as Social Networks Storage Systems

Author: Dražena Gašpar

Publisher:

Published: 2018

Total Pages: 7

ISBN-13:

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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.

The SAGE Handbook of Social Media Research Methods
The SAGE Handbook of Social Media Research Methods

Author: Luke Sloan

Publisher: SAGE

Published: 2017-01-26

Total Pages: 709

ISBN-13: 1473987210

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With coverage of the entire research process in social media, data collection and analysis on specific platforms, and innovative developments in the field, this handbook is the ultimate resource for those looking to tackle the challenges that come with doing research in this sphere.

Security and Privacy in Social Networks and Big Data
Security and Privacy in Social Networks and Big Data

Author: Xiaofeng Chen

Publisher: Springer Nature

Published: 2022-10-09

Total Pages: 372

ISBN-13: 9811972427

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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.

Big Data in Complex and Social Networks
Big Data in Complex and Social Networks

Author: My T. Thai

Publisher: CRC Press

Published: 2016-12-01

Total Pages: 335

ISBN-13: 1315396688

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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.

Social Network Data Analytics
Social Network Data Analytics

Author: Charu C. Aggarwal

Publisher: Springer Science & Business Media

Published: 2011-03-18

Total Pages: 508

ISBN-13: 1441984623

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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.