Analyzing Social Networks

Analyzing Social Networks

Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis.

Author: Stephen P Borgatti

Publisher: SAGE Publications Limited

ISBN: 1526404109

Category: Social Science

Page: 384

View: 821

Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process—including basic maths principles—without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way. In addition to the fundamentals of network analysis and the research process, this new Second Edition focuses on: Digital data and social networks like Twitter Statistical models to use in SNA, like QAP and ERGM The structure and centrality of networks Methods for cohesive subgroups/community detection Supported by new chapter exercises, a glossary, and a fully updated companion website, this text is the perfect student-friendly introduction to social network analysis.
Categories: Social Science

Analyzing Social Networks

Analyzing Social Networks

Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis.

Author: Stephen P Borgatti

Publisher: SAGE

ISBN: 9781526418487

Category: Social Science

Page: 384

View: 672

Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process -- including basic maths principles -- without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way. In addition to the fundamentals of network analysis and the research process, this new edition focuses on: Digital data and social networks like Twitter Statistical models to use in SNA, like QAP and ERGM The structure and centrality of networks Methods for cohesive subgroups/community detection Supported by new chapter exercises, a glossary, and a fully updated companion website, this edition is the perfect student-friendly introduction to social network analysis.
Categories: Social Science

Analyzing the Social Web

Analyzing the Social Web

Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book.

Author: Jennifer Golbeck

Publisher: Newnes

ISBN: 9780124058569

Category: Computers

Page: 290

View: 757

Analyzing the Social Web provides a framework for the analysis of public data currently available and being generated by social networks and social media, like Facebook, Twitter, and Foursquare. Access and analysis of this public data about people and their connections to one another allows for new applications of traditional social network analysis techniques that let us identify things like who are the most important or influential people in a network, how things will spread through the network, and the nature of peoples' relationships. Analyzing the Social Web introduces you to these techniques, shows you their application to many different types of social media, and discusses how social media can be used as a tool for interacting with the online public. Presents interactive social applications on the web, and the types of analysis that are currently conducted in the study of social media. Covers the basics of network structures for beginners, including measuring methods for describing nodes, edges, and parts of the network. Discusses the major categories of social media applications or phenomena and shows how the techniques presented can be applied to analyze and understand the underlying data. Provides an introduction to information visualization, particularly network visualization techniques, and methods for using them to identify interesting features in a network, generate hypotheses for analysis, and recognize patterns of behavior. Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book.
Categories: Computers

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL

This book is perfect for use as a course text in social network analysis or as a guide for practicing NodeXL users.

Author: Derek Hansen

Publisher: Morgan Kaufmann

ISBN: 9780128177570

Category: Computers

Page: 248

View: 168

Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Second Edition, provides readers with a thorough, practical and updated guide to NodeXL, the open-source social network analysis (SNA) plug-in for use with Excel. The book analyzes social media, provides a NodeXL tutorial, and presents network analysis case studies, all of which are revised to reflect the latest developments. Sections cover history and concepts, mapping and modeling, the detailed operation of NodeXL, and case studies, including e-mail, Twitter, Facebook, Flickr and YouTube. In addition, there are descriptions of each system and types of analysis for identifying people, documents, groups and events. This book is perfect for use as a course text in social network analysis or as a guide for practicing NodeXL users. Walks users through NodeXL while also explaining the theory and development behind each step Demonstrates how visual analytics research can be applied to SNA tools for the mass market Includes updated case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and Instagram Includes downloadable companion materials and online resources at https://www.smrfoundation.org/nodexl/teaching-with-nodexl/teaching-resources/
Categories: Computers

Mining and Analyzing Social Networks

Mining and Analyzing Social Networks

Case studies are also included in this chapter to show the performance is better than traditional means. This book will focus upon Mining and Analyzing social network.

Author: I-Hsien Ting

Publisher: Springer Science & Business Media

ISBN: 9783642134210

Category: Computers

Page: 200

View: 984

Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.
Categories: Computers

Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis

Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s.

Author: Peter J. Carrington

Publisher: Cambridge University Press

ISBN: 1139443437

Category: Social Science

Page:

View: 305

Models and Methods in Social Network Analysis, first published in 2005, 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.
Categories: Social Science

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL

This is the perfect book for anyone trying to analyze the behavior of online social networks and beyond.

Author: Derek L. Hansen

Publisher: Morgan Kaufmann Pub

ISBN: 0123822297

Category: Computers

Page: 284

View: 519

"Analyzing Social Media Networks with NodeXL provides a much needed resource for the social media research community, as it describes network theory, provides compelling examples using data sources like Twitter and Flickr, and highlights how to use a free sophisticated tool for analysis. This is the perfect book for anyone trying to analyze the behavior of online social networks and beyond." ---Adam Perer, Research Scientist, IBM Research "This book provides a basic introduction to social network analysis, followed by practical instruction and examples on gathering data from online sources, importing into Excel, and then analyzing the data through Excel. The book will be important for promoting research in the area for those in information science, sociology, cultural studies, virtual community, and e-commerce."---Caroline Haythornthwaite, PhD, Professor, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools - NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theory and information visualization into a simple tool anyone can use. This makes NodeXL of interest not only to end-users but also to researchers and students studying visual and network analytics and their application in the real world.
Categories: Computers

NetNet a Tool for Simplifying the Workflow of Analyzing Social Networks with Textual Content

NetNet  a Tool for Simplifying the Workflow of Analyzing Social Networks with Textual Content

Today’s online social networks produce a significant amount of data that contain rich information.

Author: Jun Hao

Publisher:

ISBN: OCLC:1244551216

Category: Online social networks

Page:

View: 673

Today’s online social networks produce a significant amount of data that contain rich information. A key challenge is to analyze and make sense of the data. In many application scenarios, this requires analyzing both network topology information and textual content contained in the network. However, existing network analysis tools usually focus on one of these aspects, instead of providing end-to-end solutions for this particular research scenario. Therefore, users often need to utilize several different frameworks/tools with a complex workflow. In this thesis, we present NetNet, a social network analysis tool that is specifically designed to simplify the workflow of analyzing social networks containing both complicated network structure and massive textual information. In NetNet, we model social networks as interconnected user nodes with text nodes associated with them and leverage network analysis and text mining algorithms to seamlessly perform both tasks. In addition, our design utilizes web technologies to bundle the complicated workflow of data importing, network analysis, text analysis, and result delivery with a simple and efficient user interface. We evaluate the performance of our design with multiple sets of experiments on five datasets. The result shows that our design is practically efficient and scalable. We also perform a case study with NetNet to demonstrate how the workflow of analyzing social networks with textual contents is simplified.
Categories: Online social networks

Analyzing and Securing Social Networks

Analyzing and Securing Social Networks

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 ...

Author: Bhavani Thuraisingham

Publisher: CRC Press

ISBN: 9781482243284

Category: Computers

Page: 574

View: 711

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 technologies that ensure the privacy of the participants of the network as well as provide controlled access to the information posted and exchanged by the participants. The authors explore security and privacy issues for social media systems, analyze such systems, and discuss prototypes they have developed for social media systems whose data are represented using semantic web technologies. These experimental systems have been developed at The University of Texas at Dallas. The material in this book, together with the numerous references listed in each chapter, have been used for a graduate-level course at The University of Texas at Dallas on analyzing and securing social media. Several experimental systems developed by graduate students are also provided. The book is divided into nine main sections: (1) supporting technologies, (2) basics of analyzing and securing social networks, (3) the authors’ design and implementation of various social network analytics tools, (4) privacy aspects of social networks, (5) access control and inference control for social networks, (6) experimental systems designed or developed by the authors on analyzing and securing social networks, (7) social media application systems developed by the authors, (8) secure social media systems developed by the authors, and (9) some of the authors’ exploratory work and further directions.
Categories: Computers

Sociometrics and Human Relationships

Sociometrics and Human Relationships

Sociometrics and Human Relationships translates the latest academic research into practical business strategies and techniques for social network analysis.

Author: Peter A. Gloor

Publisher: Emerald Group Publishing

ISBN: 9781787147256

Category: Business & Economics

Page: 512

View: 754

Sociometrics and Human Relationships translates the latest academic research into practical business strategies and techniques for social network analysis. This essential new title is key reading for students and practitioners across marketing, design, sociology, psychology and the humanities, and comes with a free academic license of Condor.
Categories: Business & Economics

Analyzing Social Media Data and Web Networks

Analyzing Social Media Data and Web Networks

This volume profiles the latest techniques being employed by social scientists to collect and interpret data from some of the most popular social media applications, the political parties' own online activist spaces, and the wider system of ...

Author: M. Cantijoch

Publisher: Springer

ISBN: 9781137276773

Category: Social Science

Page: 303

View: 962

As governments, citizens and organizations have moved online there is an increasing need for academic enquiry to adapt to this new context for communication and political action. This adaptation is crucially dependent on researchers being equipped with the necessary methodological tools to extract, analyze and visualize patterns of web activity. This volume profiles the latest techniques being employed by social scientists to collect and interpret data from some of the most popular social media applications, the political parties' own online activist spaces, and the wider system of hyperlinks that structure the inter-connections between these sites. Including contributions from a range of academic disciplines including Political Science, Media and Communication Studies, Economics, and Computer Science, this study showcases a new methodological approach that has been expressly designed to capture and analyze web data in the process of investigating substantive questions.
Categories: Social Science

Sentiment Analysis in Social Networks

Sentiment Analysis in Social Networks

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, ...

Author: Federico Pozzi

Publisher: Morgan Kaufmann Publishers

ISBN: 0128044128

Category:

Page: 242

View: 307

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 methodologiesProvides insights into opinion spamming, reasoning, and social network analysisShows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequencesServes 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 methodologiesProvides insights into opinion spamming, reasoning, and social network miningShows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequencesServes as a one-stop reference for the state-of-the-art in social media analytics
Categories:

Social Network Analysis An Introduction

Social Network Analysis  An Introduction

Scientific Essay from the year 2016 in the subject Sociology - Basics and General, , language: English, abstract: The concept of social networks and their methods of analysis have attracted the interest and curiosity of researchers in the ...

Author: Ioannis Panges

Publisher: GRIN Verlag

ISBN: 9783668493230

Category: Science

Page: 8

View: 545

Scientific Essay from the year 2016 in the subject Sociology - Basics and General, , language: English, abstract: The concept of social networks and their methods of analysis have attracted the interest and curiosity of researchers in the social sciences and behavioral sciences over the past decades. Most of this interest in analyzing social networks focuses on under-standing the relationships between social structures as well as the patterns and impacts of these relationships. Many researchers have recognized that the analysis of networks brings a new impetus to the answer of the classical research questions of sociology and behavioral sciences, giving precise formal definitions of the political, economic or social structural environment. From the point of view of the analysis of social networks, the social environment can be expressed through graphs in the relations between the interacting units.
Categories: Science

Graph Theoretic Approaches for Analyzing Large Scale Social Networks

Graph Theoretic Approaches for Analyzing Large Scale Social Networks

Social Network Analysis is a rapidly emerging area within the discipline of Data Science and is of immense research interest for both theory and practice.

Author: Meghanathan, Natarajan

Publisher: IGI Global

ISBN: 9781522528159

Category: Computers

Page: 355

View: 402

Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.
Categories: Computers

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL

Social network theory and analysis is a relatively recent set of ideas and methods largely developed over the past 80 years. It builds on and uses concepts ...

Author: Derek Hansen

Publisher: Morgan Kaufmann

ISBN: 0123822300

Category: Computers

Page: 304

View: 272

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
Categories: Computers

Social Networks and Trust

Social Networks and Trust

Social Networks and Trust discusses two possible explanations for the emergence of trust via social networks.

Author: Vincent Buskens

Publisher: Springer Science & Business Media

ISBN: 9780306476457

Category: Business & Economics

Page: 269

View: 766

Social Networks and Trust discusses two possible explanations for the emergence of trust via social networks. If network members can sanction untrustworthiness of actors, these actors may refrain from acting in an untrustworthy manner. Moreover, if actors are informed regularly about trustworthy behavior of others, trust will grow among these actors. A unique combination of formal model building and empirical methodology is used to derive and test hypotheses about the effects of networks on trust. The models combine elements from game theory, which is mainly used in economics, and social network analysis, which is mainly used in sociology. The hypotheses are tested (1) by analyzing contracts in information technology transactions from a survey on small and medium-sized enterprises and (2) by studying judgments of subjects in a vignette experiment related to hypothetical transactions with a used-car dealer.
Categories: Business & Economics

Learning Automata Approach for Social Networks

Learning Automata Approach for Social Networks

This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA.

Author: Alireza Rezvanian

Publisher: Springer

ISBN: 9783030107673

Category: Computers

Page: 329

View: 865

This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions among individuals and in the networks’ evolution, and to develop the algorithms required for meaningful analysis. As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.
Categories: Computers

Introduction to Social Network Analysis with R

Introduction to Social Network Analysis with R

These numerous examples and case studies reveal how R can be used as a convenient simulation platform, and are accompanied by a supporting website featuring R functions and datasets used throughout the book.

Author: Michal Bojanowski

Publisher: John Wiley & Sons

ISBN: 1118456041

Category:

Page: 350

View: 485

Introduction to Social Network Analysis with R provides an introduction to performing SNA studies using R, combining the theories of social networks and methods of social network analysis with the R environment as an open source system for statistical data analysis and graphics. Short introductions to both R and the topics of SNA are included, making the book accessible to those with little or no familiarity with either domain. The topics covered and the structure of the book mimic the stages of a typical SNA research project, and include chapters devoted to data importing, network data manipulation and selection, network visualisation and methods of de­scriptive SNA. Concepts of SNA are introduced and their application demonstrated with an extensive use of empirical examples which are based on a variety of real network datasets. Introduction to Social Network Analysis with R also provides background and theoretical motivations, which include examples of important theoretical models behind the presented methods. These numerous examples and case studies reveal how R can be used as a convenient simulation platform, and are accompanied by a supporting website featuring R functions and datasets used throughout the book.
Categories:

Evolution of Social Networks

Evolution of Social Networks

This book answers the question of whether we can apply evolutionary theories to our understanding of the development of social structures.

Author: Patrick Doreian

Publisher: Routledge

ISBN: 9781136647321

Category: Social Science

Page: 272

View: 409

This book answers the question of whether we can apply evolutionary theories to our understanding of the development of social structures. Social networks have increasingly become the focus of many social scientists as a way of analyzing these social structures. While many powerful network analytic tools have been developed and applied to a wide range of empirical phenomena, understanding the evolution of social organization still requires theories and analyses of social network evolutionary processes. Researchers from a variety of disciplines have combined their efforts in what is an indication of some very promising future research and the work represented in this volume provides a basis for a sustained analysis of the evolution of social life.
Categories: Social Science