Social Network Analytics

Social Network Analytics
Author: Nilanjan Dey,Samarjeet Borah,Rosalina Babo,Amira Ashour
Publsiher: Academic Press
Total Pages: 220
Release: 2019-01-15
ISBN 10: 9780128154588
ISBN 13: 0128154586
Language: EN, FR, DE, ES & NL

Social Network Analytics Book Review:

Analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network. The analysis of social network data involves, basically, mapping and measuring the relationships and flows between people, groups, organizations, computers, URLs, and other connected information and knowledge entities. It is a difficult task due to availability of huge amounts of data along with very complex structures. Social Network Analytics focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, the book includes a variety of applications from several domains, such as scientific research, business, and industrial. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, big data analytics of social networks, multidimensional scaling, and more! Examines a variety of data analytic techniques applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains

Social Network Analysis

Social Network Analysis
Author: Song Yang,Franziska B. Keller,Lu Zheng
Publsiher: SAGE Publications
Total Pages: 248
Release: 2016-10-28
ISBN 10: 1506362125
ISBN 13: 9781506362120
Language: EN, FR, DE, ES & NL

Social Network Analysis Book Review:

Social Network Analysis: Methods and Examples by Song Yang, Franziska B. Keller, and Lu Zheng prepares social science students to conduct their own social network analysis (SNA) by covering basic methodological tools along with illustrative examples from various fields. This innovative book takes a conceptual rather than a mathematical approach as it discusses the connection between what SNA methods have to offer and how those methods are used in research design, data collection, and analysis. Four substantive applications chapters provide examples from politics, work and organizations, mental and physical health, and crime and terrorism studies.

Social Network Analytics for Contemporary Business Organizations

Social Network Analytics for Contemporary Business Organizations
Author: Bansal, Himani,Shrivastava, Gulshan,Nguyen, Gia Nhu,Stanciu, Loredana-Mihaela
Publsiher: IGI Global
Total Pages: 321
Release: 2018-03-23
ISBN 10: 1522550984
ISBN 13: 9781522550983
Language: EN, FR, DE, ES & NL

Social Network Analytics for Contemporary Business Organizations Book Review:

Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.

Social Network Data Analytics

Social Network Data Analytics
Author: Charu C. Aggarwal
Publsiher: Springer Science & Business Media
Total Pages: 502
Release: 2011-03-18
ISBN 10: 1441984623
ISBN 13: 9781441984623
Language: EN, FR, DE, ES & NL

Social Network Data Analytics Book Review:

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.

Social Network Analysis

Social Network Analysis
Author: Stanley Wasserman,Katherine Faust,Stanley (University of Illinois Wasserman, Urbana-Champaign)
Publsiher: Cambridge University Press
Total Pages: 825
Release: 1994-11-25
ISBN 10: 9780521387071
ISBN 13: 0521387078
Language: EN, FR, DE, ES & NL

Social Network Analysis Book Review:

Covers methods for the analysis of social networks and applies them to examples.

Big Data Analytics

Big Data Analytics
Author: Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
Publsiher: CRC Press
Total Pages: 316
Release: 2018-12-12
ISBN 10: 1351622587
ISBN 13: 9781351622585
Language: EN, FR, DE, ES & NL

Big Data Analytics Book Review:

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 ofbig 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.

Applied Social Network Analysis With R Emerging Research and Opportunities

Applied Social Network Analysis With R  Emerging Research and Opportunities
Author: Gençer, Mehmet
Publsiher: IGI Global
Total Pages: 284
Release: 2020-02-07
ISBN 10: 1799819140
ISBN 13: 9781799819141
Language: EN, FR, DE, ES & NL

Applied Social Network Analysis With R Emerging Research and Opportunities Book Review:

Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research. Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the issue of structure in terms of its effects on human societies and the state of the individuals in these communities. Even though the theme of the book is business-oriented, an approach underlining and strengthening the ties of this field of study with social sciences for further development is adopted throughout. Therefore, the knowledge presented is valid for analyzing not only the organization of the business world but also for the organization of any given community. Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking coverage on analyzing social and business networks using modern methods of statistics, programming, and data sets.

Social Network Analysis

Social Network Analysis
Author: John Scott
Publsiher: SAGE
Total Pages: 224
Release: 2000-01-26
ISBN 10: 1446236161
ISBN 13: 9781446236161
Language: EN, FR, DE, ES & NL

Social Network Analysis Book Review:

The revised and updated edition of this bestselling text provides an accessible introduction to the theory and practice of network analysis in the social sciences. It gives a clear and authoritative guide to the general framework of network analysis, explaining the basic concepts, technical measures and reviewing the available computer programs. The book outlines both the theoretical basis of network analysis and the key techniques for using it as a research tool. Building upon definitions of points, lines and paths, John Scott demonstrates their use in clarifying such measures as density, fragmentation and centralization. He identifies the various cliques, components and circles into which networks are formed, and outlines an approach to the study of socially structured positions. He also discusses the use of multidimensional methods for investigating social networks. Social Network Analysis is an invaluable resource for researchers across the social sciences and for students of social theory and research methods.

Sentiment Analysis in Social Networks

Sentiment Analysis in Social Networks
Author: Federico Alberto Pozzi,Elisabetta Fersini,Enza Messina,Bing Liu
Publsiher: Morgan Kaufmann
Total Pages: 284
Release: 2016-10-06
ISBN 10: 0128044381
ISBN 13: 9780128044384
Language: EN, FR, DE, ES & NL

Sentiment Analysis in Social Networks Book Review:

The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics

Social Network Analysis for Startups

Social Network Analysis for Startups
Author: Maksim Tsvetovat,Alexander Kouznetsov
Publsiher: "O'Reilly Media, Inc."
Total Pages: 190
Release: 2011-10-06
ISBN 10: 1449306462
ISBN 13: 9781449306465
Language: EN, FR, DE, ES & NL

Social Network Analysis for Startups Book Review:

SNA techniques are derived from sociological and social-psychological theories and take into account the whole network (or, in case of very large networks such as Twitter -- a large segment of the network). Thus, we may arrive at results that may seem counter-intuitive -- e.g. that Jusin Bieber (7.5 mil. followers) and Lady Gaga (7.2 mil. followers) have relatively little actual influence despite their celebrity status -- while a middle-of-the-road blogger with 30K followers is able to generate tweets that "go viral" and result in millions of impressions. O'Reilly's "Mining Social Media" and "Programming Collective Intelligence" books are an excellent start for people inteseted in SNA. This book builds on these books' foundations to teach a new, pragmatic, way of doing SNA. I would like to write a book that links theory ("why is this important?", "how do various concepts interact?", "how do I interpret quantitative results?") and practice -- gathering, analyzing and visualizing data using Python and other open-source tools.

Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis
Author: Peter J. Carrington,John Scott,Stanley Wasserman
Publsiher: Unknown
Total Pages: 328
Release: 2005-02-07
ISBN 10: 9780521809597
ISBN 13: 0521809592
Language: EN, FR, DE, ES & NL

Models and Methods in Social Network Analysis Book Review:

Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.

Knowledge Solutions

Knowledge Solutions
Author: Olivier Serrat
Publsiher: Springer
Total Pages: 1140
Release: 2017-05-22
ISBN 10: 981100983X
ISBN 13: 9789811009839
Language: EN, FR, DE, ES & NL

Knowledge Solutions Book Review:

This book is open access under a CC BY-NC 3.0 IGO license. This book comprehensively covers topics in knowledge management and competence in strategy development, management techniques, collaboration mechanisms, knowledge sharing and learning, as well as knowledge capture and storage. Presented in accessible “chunks,” it includes more than 120 topics that are essential to high-performance organizations. The extensive use of quotes by respected experts juxtaposed with relevant research to counterpoint or lend weight to key concepts; “cheat sheets” that simplify access and reference to individual articles; as well as the grouping of many of these topics under recurrent themes make this book unique. In addition, it provides scalable tried-and-tested tools, method and approaches for improved organizational effectiveness. The research included is particularly useful to knowledge workers engaged in executive leadership; research, analysis and advice; and corporate management and administration. It is a valuable resource for those working in the public, private and third sectors, both in industrialized and developing countries.

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL
Author: Derek Hansen,Ben Shneiderman,Marc A. Smith
Publsiher: Morgan Kaufmann
Total Pages: 304
Release: 2010-09-14
ISBN 10: 9780123822307
ISBN 13: 0123822300
Language: EN, FR, DE, ES & NL

Analyzing Social Media Networks with NodeXL Book Review:

Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology. This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies. Part I provides background in the history and concepts of social media and social networks. Also included here is social network analysis, which flows from measuring, to mapping, and modeling collections of connections. The next part focuses on the detailed operation of the free and open-source NodeXL extension of Microsoft Excel, which is used in all exercises throughout this book. In the final part, each chapter presents one form of social media, such as e-mail, Twitter, Facebook, Flickr, and Youtube. In addition, there are descriptions of each system, the nature of networks when people interact, and types of analysis for identifying people, documents, groups, and events. Walks you through NodeXL, while explaining the theory and development behind each step, providing takeaways that can apply to any SNA Demonstrates how visual analytics research can be applied to SNA tools for the mass market Includes case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and wikis Download companion materials and resources at https://nodexl.codeplex.com/documentation

Social Networks Analysis and Case Studies

Social Networks  Analysis and Case Studies
Author: Şule Gündüz-Öğüdücü,A. Şima Etaner-Uyar
Publsiher: Springer
Total Pages: 249
Release: 2014-07-11
ISBN 10: 3709117976
ISBN 13: 9783709117972
Language: EN, FR, DE, ES & NL

Social Networks Analysis and Case Studies Book Review:

The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many opportunities in different application domains. Forming a bridge between theory and applications makes this work appealing to both academics and practitioners as well as graduate students.

Social Network Analysis in Telecommunications

Social Network Analysis in Telecommunications
Author: Carlos Andre Reis Pinheiro
Publsiher: John Wiley & Sons
Total Pages: 304
Release: 2011-05-09
ISBN 10: 1118010957
ISBN 13: 9781118010952
Language: EN, FR, DE, ES & NL

Social Network Analysis in Telecommunications Book Review:

A timely look at effective use of social network analysis within the telecommunications industry to boost customer relationships The key to any successful company is the relationship that it builds with its customers. This book shows how social network analysis, analytics, and marketing knowledge can be combined to create a positive customer experience within the telecommunications industry. Reveals how telecommunications companies can effectively enhance their relationships with customers Provides the groundwork for defining social network analysis Defines the tools that can be used to address social network problems A must-read for any professionals eager to distinguish their products in the marketplace, this book shows you how to get it done right, with social network analysis.

Exploratory Social Network Analysis with Pajek

Exploratory Social Network Analysis with Pajek
Author: Wouter de Nooy,Andrej Mrvar,Vladimir Batagelj
Publsiher: Cambridge University Press
Total Pages: 334
Release: 2005-01-10
ISBN 10: 9780521841733
ISBN 13: 0521841739
Language: EN, FR, DE, ES & NL

Exploratory Social Network Analysis with Pajek Book Review:

This is the first textbook on social network analysis integrating theory, applications, and professional software for performing network analysis. The book introduces the main concepts and their applications in social research with exercises. An application section explaining how to perform the network analyses with Pajek software follows each theoretical section.

Predictive Analytics Data Mining and Big Data

Predictive Analytics  Data Mining and Big Data
Author: S. Finlay
Publsiher: Springer
Total Pages: 260
Release: 2014-07-01
ISBN 10: 1137379286
ISBN 13: 9781137379283
Language: EN, FR, DE, ES & NL

Predictive Analytics Data Mining and Big Data Book Review:

This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.

Social Network Mining Analysis and Research Trends Techniques and Applications

Social Network Mining  Analysis  and Research Trends  Techniques and Applications
Author: Ting, I-Hsien
Publsiher: IGI Global
Total Pages: 501
Release: 2011-12-31
ISBN 10: 1613505140
ISBN 13: 9781613505144
Language: EN, FR, DE, ES & NL

Social Network Mining Analysis and Research Trends Techniques and Applications Book Review:

"This book covers current research trends in the area of social networks analysis and mining, sharing research from experts in the social network analysis and mining communities, as well as practitioners from social science, business, and computer science"--Provided by publisher.

Social Media Data Mining and Analytics

Social Media Data Mining and Analytics
Author: Gabor Szabo,Gungor Polatkan,P. Oscar Boykin,Antonios Chalkiopoulos
Publsiher: John Wiley & Sons
Total Pages: 352
Release: 2018-09-19
ISBN 10: 111882489X
ISBN 13: 9781118824894
Language: EN, FR, DE, ES & NL

Social Media Data Mining and Analytics Book Review:

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.

Fraud Analytics Using Descriptive Predictive and Social Network Techniques

Fraud Analytics Using Descriptive  Predictive  and Social Network Techniques
Author: Bart Baesens,Wouter Verbeke,Veronique Van Vlasselaer
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2015-08-17
ISBN 10: 1119133122
ISBN 13: 9781119133124
Language: EN, FR, DE, ES & NL

Fraud Analytics Using Descriptive Predictive and Social Network Techniques Book Review:

Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post–implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti–money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.