Models and Methods in Social Network Analysis
Models and Methods in Social Network Analysis

Author: Peter J. Carrington

Publisher:

Published: 2005-02-07

Total Pages: 328

ISBN-13: 9780521809597

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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.

Agent-Based Modeling and Network Dynamics
Agent-Based Modeling and Network Dynamics

Author: Akira Namatame

Publisher: Oxford University Press

Published: 2016-01-28

Total Pages: 294

ISBN-13: 0191074993

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While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.

Data Mining in Dynamic Social Networks and Fuzzy Systems
Data Mining in Dynamic Social Networks and Fuzzy Systems

Author: Bhatnagar, Vishal

Publisher: IGI Global

Published: 2013-06-30

Total Pages: 412

ISBN-13: 1466642149

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Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data. Data Mining in Dynamic Social Networks and Fuzzy Systems brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organizational development.

Trends in Social Network Analysis
Trends in Social Network Analysis

Author: Rokia Missaoui

Publisher: Springer

Published: 2017-04-29

Total Pages: 263

ISBN-13: 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.

Dynamic Network Theory
Dynamic Network Theory

Author: James D. Westaby

Publisher: American Psychological Association (APA)

Published: 2012

Total Pages: 0

ISBN-13: 9781433810824

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Social networks surround us. They are as diverse as a local community trying to help solve a neighborhood crime, a firm wondering how to streamline decision making, or a terrorist cell figuring out how to plan an attack without central coordination. This groundbreaking book explores social networks in formal and informal organizations, using a combination of approaches from social psychology, I/O psychology, organization/management science, social learning, and helping skills. A quantum advance over conventional social network analysis, Dynamic Network Theory examines how social networks articulate goals and generate social capital at various levels. Geared for researchers and practitioners, Dynamic Network Theory is also written for graduate students and advanced undergraduate students. Appendixes include primers on designing and analyzing dynamic network charts.

Dynamic Social Network Modeling and Analysis
Dynamic Social Network Modeling and Analysis

Author: National Research Council

Publisher: National Academies Press

Published: 2003-08-01

Total Pages: 393

ISBN-13: 0309089522

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In the summer of 2002, the Office of Naval Research asked the Committee on Human Factors to hold a workshop on dynamic social network and analysis. The primary purpose of the workshop was to bring together scientists who represent a diversity of views and approaches to share their insights, commentary, and critiques on the developing body of social network analysis research and application. The secondary purpose was to provide sound models and applications for current problems of national importance, with a particular focus on national security. This workshop is one of several activities undertaken by the National Research Council that bears on the contributions of various scientific disciplines to understanding and defending against terrorism. The presentations were grouped in four sessions â€" Social Network Theory Perspectives, Dynamic Social Networks, Metrics and Models, and Networked Worlds â€" each of which concluded with a discussant-led roundtable discussion among the presenters and workshop attendees on the themes and issues raised in the session.

Sentiment Analysis in Social Networks
Sentiment Analysis in Social Networks

Author: Federico Alberto Pozzi

Publisher: Morgan Kaufmann

Published: 2016-10-06

Total Pages: 286

ISBN-13: 0128044381

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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

Diffusion in Social Networks
Diffusion in Social Networks

Author: Paulo Shakarian

Publisher: Springer

Published: 2015-09-16

Total Pages: 110

ISBN-13: 3319231057

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This book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), sociology (tipping models), physics (voter models), biology (evolutionary models), and epidemiology (SIR/SIS and related models). A variety of properties and problems related to these models are discussed including identifying seeds sets to initiate diffusion, game theoretic problems, predicting diffusion events, and more. The book explores numerous connections between social network diffusion research and artificial intelligence through topics such as agent-based modeling, logic programming, game theory, learning, and data mining. The book also surveys key empirical results in social network diffusion, and reviews the classic and cutting-edge research with a focus on open problems.

Perspectives on Social Network Research
Perspectives on Social Network Research

Author: Paul W. Holland

Publisher: Elsevier

Published: 2013-10-22

Total Pages: 545

ISBN-13: 148326050X

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Perspectives on Social Network Research covers the proceedings of the Mathematical Social Science Board's Advanced Research Symposium on Social Networks held at Dartmouth College, Hanover, New Hampshire, on September 18-21, 1975. This symposium was organized to survey research on social networks as well as review and criticize major research thrusts involving network studies of social behavior. The book covers topics such as the Davis/Holland/Leinhardt studies, structural sociometry, network analysis of the diffusion of innovations, and the deterministic models of social networks. Also covered are topics such as structural control models for group processes, social clusters and opinion clusters, equilibrating processes in social networks, and estimation of population totals by use of snowball samples. The text is recommended for sociologists, anthropologists, and psychologists, especially those who would like to know more about social network and are currently engaged in research in that particular field.

Social Influence Network Theory
Social Influence Network Theory

Author: Noah E. Friedkin

Publisher: Cambridge University Press

Published: 2011-04-18

Total Pages: 390

ISBN-13: 9781107002463

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Social influence network theory presents a mathematical formalization of the social process of attitude changes that unfolds in a social network of interpersonal influences. This book brings the theory to bear on lines of research in the domain of small group dynamics concerned with changes of group members' positions on an issue, including the formation of consensus and of settled disagreement, via endogenous interpersonal influences, in which group members are responding to the displayed positions of the members of the group. Social influence network theory advances a dynamic social cognition mechanism, in which individuals are weighing and combining their own and others' positions on an issue in the revision of their own positions. The influence network construct of the theory is the social structure of the endogenous interpersonal influences that are involved in this mechanism. With this theory, the authors seek to lay the foundation for a better formal integration of classical and current lines of work on small groups in psychological and sociological social psychology.