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Trends in Social Network Analysis

Trends in Social Network Analysis
Author: Rokia Missaoui
Publisher: Springer
Total Pages: 255
Release: 2017-04-29
Genre: Computers
ISBN: 3319534203

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The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.


Social Networking

Social Networking
Author: Xin M. Tu
Publisher: Nova Science Publishers
Total Pages: 0
Release: 2013
Genre: Online social networks
ISBN: 9781628085297

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Social networking focuses on social relationships (eg: friendships) diagrammed as nodes (points) and links (ties or edges between points). Social network analysis (SNA) examines features of such relationships within a social networking system, including how such social interactions change over time. SNA can measure and map connectedness or flow (eg: information, resources, etc.) within and across individuals, groups, and organisations. SNA can examine these ties in virtual- or geo-temporal spaces -- yielding rich mixed methods possibilities and wide application to a host of scientific phenomena. The advent of social media established a cultural meme that carries social network concepts to broader public audiences, and that reinforces SNAs path to be a powerful interdisciplinary approach. Google Ngram viewer shows the use of social network analysis in the corpus of books burgeoned in the late 1960s, and has continued to grow exponentially since the 1990s. The conceptual and methodological reach now extends both widely -- across scientific disciplines -- and deeply -- as field advances arise with the rapid pace of new inquiries.Facing this tremendous promulgation and diversification of SNA, this book distills essential frontiers across fields. Introducing emerging issues in the application of social network theory and SNA, and how these can or will be addressed, each chapter illuminates new trends or applications of a social network approach that can have wide potential impact in other disciplines. Conceptual advances (eg: applying the concepts of social networks such as peer influence on disease management and treatment adherence), as well as novel analytic approaches for studying properties of social networks are highlighted.


Social Network Mining, Analysis, and Research Trends

Social Network Mining, Analysis, and Research Trends
Author: I-Hsien Ting
Publisher:
Total Pages: 407
Release: 2012
Genre: Data mining
ISBN: 9781613505151

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"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.


Computational Social Network Analysis

Computational Social Network Analysis
Author: Ajith Abraham
Publisher: Springer
Total Pages: 0
Release: 2012-03-01
Genre: Computers
ISBN: 9781447125327

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Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems. Topics and Features: Provides an overview social network tools, and explores methods for discovering key players in social networks, designing self-organizing search systems, and clustering blog sites, surveys techniques for exploratory analysis and text mining of social networks, approaches to tracking online community interaction, and examines how the topological features of a system affects the flow of information, reviews the models of network evolution, covering scientific co-citation networks, nature-inspired frameworks, latent social networks in e-Learning systems, and compound communities, examines the relationship between the intent of web pages, their architecture and the communities who take part in their usage and creation, discusses team selection based on members’ social context, presents social network applications, including music recommendation and face recognition in photographs, explores the use of social networks in web services that focus on the discovery stage in the life cycle of these web services. This useful and comprehensive volume will be indispensible to senior undergraduate and postgraduate students taking courses in Social Intelligence, as well as to researchers, developers, and postgraduates interested in intelligent-social-networks research and related areas.


Social Network Analysis for Startups

Social Network Analysis for Startups
Author: Maksim Tsvetovat
Publisher: "O'Reilly Media, Inc."
Total Pages: 191
Release: 2011-10-06
Genre: Business & Economics
ISBN: 1449306462

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Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available. Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA researchers, you'll learn concepts and techniques for recognizing patterns in social media, political groups, companies, cultural trends, and interpersonal networks. You'll also learn how to use Python and other open source tools—such as NetworkX, NumPy, and Matplotlib—to gather, analyze, and visualize social data. This book is the perfect marriage between social network theory and practice, and a valuable source of insight and ideas. Discover how internal social networks affect a company’s ability to perform Follow terrorists and revolutionaries through the 1998 Khobar Towers bombing, the 9/11 attacks, and the Egyptian uprising Learn how a single special-interest group can control the outcome of a national election Examine relationships between companies through investment networks and shared boards of directors Delve into the anatomy of cultural fads and trends—offline phenomena often mediated by Twitter and Facebook


New Directions in Web Data Management 1

New Directions in Web Data Management 1
Author: Athena Vakali
Publisher: Springer Science & Business Media
Total Pages: 357
Release: 2011-01-19
Genre: Computers
ISBN: 3642175503

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This book addresses the major issues in the Web data management related to technologies and infrastructures, methodologies and techniques as well as applications and implementations. Emphasis is placed on Web engineering and technologies, Web graph managing, searching and querying and the importance of social Web.


State of the Art Applications of Social Network Analysis

State of the Art Applications of Social Network Analysis
Author: Fazli Can
Publisher: Springer
Total Pages: 375
Release: 2014-05-14
Genre: Computers
ISBN: 3319059122

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Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.


Advanced Data Mining and Applications

Advanced Data Mining and Applications
Author: Longbing Cao
Publisher: Springer Science & Business Media
Total Pages: 589
Release: 2010-11-05
Genre: Computers
ISBN: 3642173128

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This book constitutes the refereed proceedings of the 6th International Conference on Advanced Data Mining and Applications, ADMA 2010, held in Chongqing, China, in November 2010. 63 carefully reviewed regular papers and 55 revised short papers were presented. The papers are organized in topical sections on data mining foundations; data mining in specific areas; data mining methodologies and processes; and data mining applications and systems.


Social Network Data Analytics

Social Network Data Analytics
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
Total Pages: 508
Release: 2011-03-18
Genre: Computers
ISBN: 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.


Knowledge Management in Construction

Knowledge Management in Construction
Author: Chimay J. Anumba
Publisher: John Wiley & Sons
Total Pages: 243
Release: 2008-04-15
Genre: Technology & Engineering
ISBN: 0470759526

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A key problem facing the construction industry is that all work is done by transient project teams, and in the past there has been no structured approach to learning from projects once they are completed. Now, though, the industry is adapting concepts of knowledge management to improve the situation. This book brings together 13 contributors from research and industry to show how managing construction knowledge can bring real benefits to organisations and projects. It covers a wide range of issues, from basic definitions and fundamental concepts, to the role of information technology, and engendering a knowledge sharing culture. Practical examples from construction and other industry sectors are used throughout to illustrate the various dimensions of knowledge management. The challenges of implementing knowledge management are outlined and the ensuing benefits highlighted.