A User’s Guide to Network Analysis in R PDF Download
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Author: Douglas Luke
Publisher: Springer
ISBN: 3319238833
Category : Mathematics
Languages : en
Pages : 241
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Book Description
Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.
Author: Douglas Luke
Publisher: Springer
ISBN: 3319238833
Category : Mathematics
Languages : en
Pages : 241
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Book Description
Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.
Author: Stephen P. Borgatti
Publisher: Sage Publications Limited
ISBN: 9781529722482
Category : Social Science
Languages : en
Pages : 472
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Book Description
This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: Discusses a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks Provides a fully integrated discussion of digital data and networks like Twitter, sociolab and Amazon Offers digital resources like practice datasets and worked examples that help you get to grips with R software
Author: Yanchang Zhao
Publisher: Academic Press
ISBN: 012397271X
Category : Mathematics
Languages : en
Pages : 251
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Book Description
R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work
Author: Eric D. Kolaczyk
Publisher: Springer
ISBN: 1493909835
Category : Computers
Languages : en
Pages : 214
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Book Description
Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
Author: Michal Bojanowski
Publisher: John Wiley & Sons
ISBN: 9781118456040
Category :
Languages : en
Pages : 0
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Book Description
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.
Author: Mohammad Gouse Galety
Publisher: John Wiley & Sons
ISBN: 1119836735
Category : Technology & Engineering
Languages : en
Pages : 260
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Book Description
SOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an underlying social network to achieve widespread adoption. Network analysis that offers an appreciation method to health systems and services to illustrate, diagnose, and analyze networks in health systems. The social web has developed a significant social and interactive data source that pays exceptional attention to social science and humanities research. The benefits of artificial intelligence enable social media platforms to meet an increasing number of users and yield the biggest marketplace, thus helping social networking analysis distribute better customer understanding and aiding marketers to target the right customers. Audience The book will interest computer scientists, AI researchers, IT and software engineers, mathematicians.
Author: Adela-Maria Isvoranu
Publisher: Taylor & Francis
ISBN: 100054107X
Category : Psychology
Languages : en
Pages : 261
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Book Description
A systematic, innovative introduction to the field of network analysis, Network Psychometrics with R: A Guide for Behavioral and Social Scientists provides a comprehensive overview of and guide to both the theoretical foundations of network psychometrics as well as modelling techniques developed from this perspective. Written by pioneers in the field, this textbook showcases cutting-edge methods in an easily accessible format, accompanied by problem sets and code. After working through this book, readers will be able to understand the theoretical foundations behind network modelling, infer network topology, and estimate network parameters from different sources of data. This book features an introduction on the statistical programming language R that guides readers on how to analyse network structures and their stability using R. While Network Psychometrics with R is written in the context of social and behavioral science, the methods introduced in this book are widely applicable to data sets from related fields of study. Additionally, while the text is written in a non-technical manner, technical content is highlighted in textboxes for the interested reader. Network Psychometrics with R is ideal for instructors and students of undergraduate and graduate level courses and workshops in the field of network psychometrics as well as established researchers looking to master new methods. This book is accompanied by a companion website with resources for both students and lecturers.
Author: Maksim Tsvetovat
Publisher: "O'Reilly Media, Inc."
ISBN: 1449306462
Category : Business & Economics
Languages : en
Pages : 191
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Book Description
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
Author: Ryan A. Estrellado
Publisher: Routledge
ISBN: 1000200906
Category : Education
Languages : en
Pages : 331
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Book Description
Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
Author:
Publisher: Engineering Science Reference
ISBN: 9781799819158
Category : Computers
Languages : en
Pages : 0
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Book Description
"This book explores the structure of socio-economic relations, in particular, relations in business life"--
