Trends In Social Network Analysis

Download or read book Trends in Social Network Analysis written by Rokia Missaoui and published by Springer. This book was released on 2017-04-29 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Social Networking written by Xin M. Tu and published by Nova Science Publishers. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Social Network Analysis for Startups written by Maksim Tsvetovat and published by "O'Reilly Media, Inc.". This book was released on 2011-10-06 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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 New Directions in Web Data Management 1 written by Athena Vakali and published by Springer Science & Business Media. This book was released on 2011-01-19 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Social Behaviour written by Tamás Székely and published by Cambridge University Press. This book was released on 2010-11-18 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive analysis of the genetic, ecological and phylogenetic aspects of social behaviour, by experts in the field.

Download or read book Sentiment Analysis in Social Networks written by Federico Alberto Pozzi and published by Morgan Kaufmann. This book was released on 2016-10-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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