Download or read book Working with Network Data written by James Bagrow and published by Cambridge University Press. This book was released on 2024-05-31 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing examples from real-world networks, this essential book traces the methods behind network analysis and explains how network data is first gathered, then processed and interpreted. The text will equip you with a toolbox of diverse methods and data modelling approaches, allowing you to quickly start making your own calculations on a huge variety of networked systems. This book sets you up to succeed, addressing the questions of what you need to know and what to do with it, when beginning to work with network data. The hands-on approach adopted throughout means that beginners quickly become capable practitioners, guided by a wealth of interesting examples that demonstrate key concepts. Exercises using real-world data extend and deepen your understanding, and develop effective working patterns in network calculations and analysis. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise.

Download or read book Network Models for Data Science written by Alan Julian Izenman and published by Cambridge University Press. This book was released on 2022-12-31 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to describe modern methods for analyzing complex networks arising from a wide range of disciplines.

Download or read book ggplot2 written by Hadley Wickham and published by Springer Science & Business Media. This book was released on 2009-10-03 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures

Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

Download or read book Network Analysis written by Ulrik Brandes and published by Springer. This book was released on 2005-02-02 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: ‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.

Download or read book Handbook of Graphs and Networks in People Analytics written by Keith McNulty and published by CRC Press. This book was released on 2022-06-19 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.

Download or read book Networks Crowds and Markets written by David Easley and published by Cambridge University Press. This book was released on 2010-07-19 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are all film stars linked to Kevin Bacon? Why do the stock markets rise and fall sharply on the strength of a vague rumour? How does gossip spread so quickly? Are we all related through six degrees of separation? There is a growing awareness of the complex networks that pervade modern society. We see them in the rapid growth of the internet, the ease of global communication, the swift spread of news and information, and in the way epidemics and financial crises develop with startling speed and intensity. This introductory book on the new science of networks takes an interdisciplinary approach, using economics, sociology, computing, information science and applied mathematics to address fundamental questions about the links that connect us, and the ways that our decisions can have consequences for others.

Download or read book Heterogeneous Information Network Analysis and Applications written by Chuan Shi and published by Springer. This book was released on 2017-05-25 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data. Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking or pattern recognition.

Download or read book Network Science with Python written by David Knickerbocker and published by Packt Publishing Ltd. This book was released on 2023-02-28 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the use of graph networks to develop a new approach to data science using theoretical and practical methods with this expert guide using Python, printed in color Key FeaturesCreate networks using data points and informationLearn to visualize and analyze networks to better understand communitiesExplore the use of network data in both - supervised and unsupervised machine learning projectsPurchase of the print or Kindle book includes a free PDF eBookBook Description Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You'll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You'll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you'll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You'll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you'll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you. What you will learnExplore NLP, network science, and social network analysisApply the tech stack used for NLP, network science, and analysisExtract insights from NLP and network dataGenerate personalized NLP and network projectsAuthenticate and scrape tweets, connections, the web, and data streamsDiscover the use of network data in machine learning projectsWho this book is for Network Science with Python demonstrates how programming and social science can be combined to find new insights. Data scientists, NLP engineers, software engineers, social scientists, and data science students will find this book useful. An intermediate level of Python programming is a prerequisite. Readers from both – social science and programming backgrounds will find a new perspective and add a feather to their hat.

Download or read book Data Analytics for IT Networks written by John Garrett and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Network Data Analytics written by K. G. Srinivasa and published by Springer. This book was released on 2018-04-26 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.

Download or read book A First Course in Network Theory written by Ernesto Estrada and published by OUP Oxford. This book was released on 2015-03-27 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and sociology. This book promotes the diverse nature of the study of complex networks by balancing the needs of students from very different backgrounds. It references the most commonly used concepts in network theory, provides examples of their applications in solving practical problems, and clear indications on how to analyse their results. In the first part of the book, students and researchers will discover the quantitative and analytical tools necessary to work with complex networks, including the most basic concepts in network and graph theory, linear and matrix algebra, as well as the physical concepts most frequently used for studying networks. They will also find instruction on some key skills such as how to proof analytic results and how to manipulate empirical network data. The bulk of the text is focused on instructing readers on the most useful tools for modern practitioners of network theory. These include degree distributions, random networks, network fragments, centrality measures, clusters and communities, communicability, and local and global properties of networks. The combination of theory, example and method that are presented in this text, should ready the student to conduct their own analysis of networks with confidence and allow teachers to select appropriate examples and problems to teach this subject in the classroom.

Download or read book Network Science with Python and NetworkX Quick Start Guide written by Edward L. Platt and published by Packt Publishing Ltd. This book was released on 2019-04-26 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Manipulate and analyze network data with the power of Python and NetworkX Key FeaturesUnderstand the terminology and basic concepts of network scienceLeverage the power of Python and NetworkX to represent data as a networkApply common techniques for working with network data of varying sizesBook Description NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use. If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts. By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems. What you will learnUse Python and NetworkX to analyze the properties of individuals and relationshipsEncode data in network nodes and edges using NetworkXManipulate, store, and summarize data in network nodes and edgesVisualize a network using circular, directed and shell layoutsFind out how simulating behavior on networks can give insights into real-world problemsUnderstand the ongoing impact of network science on society, and its ethical considerationsWho this book is for If you are a programmer or data scientist who wants to manipulate and analyze network data in Python, this book is perfect for you. Although prior knowledge of network science is not necessary, some Python programming experience will help you understand the concepts covered in the book easily.

Download or read book Connecting Networks Companion Guide written by Cisco Networking Academy and published by Pearson Education. This book was released on 2014 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This course discusses the WAN technologies and network services required by converged applications in a complex network. The course allows you to understand the selection criteria of network devices and WAN technologies to meet network requirements. You will learn how to configure and troubleshoot network devices and resolve common issues with data link protocols. You will also develop the knowledge and skills needed to implement IPSec and virtual private network (VPN) operations in a complex network."--Back cover.

Download or read book Business Data Communications and Networking written by Jerry FitzGerald and published by John Wiley & Sons. This book was released on 2020-12-03 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Data Communications and Networking, 14th Edition presents a classroom-tested approach to the subject, combining foundational concepts, practical exercises, and real-world case studies. The text provides a balanced, well-rounded presentation of data communications while highlighting its importance to nearly every aspect of modern business. This fully-updated new edition helps students understand how networks work and what is required to build and manage scalable, mobile, and secure networks. Clear, student-friendly chapters introduce, explain, and summarize fundamental concepts and applications such as server architecture, network and transport layers, network design processes and tools, wired and wireless networking, and network security and management. An array of pedagogical features teaches students how to select the appropriate technologies necessary to build and manage networks that meet organizational needs, maximize competitive advantage, and protect networks and data from cybersecurity threats. Discussions of real-world management and technical issues, from improving device performance to assessing and controlling costs, provide students with insight into the daily networking operations of actual businesses.

Download or read book The Sage Handbook of Social Network Analysis written by John McLevey and published by SAGE Publications Limited. This book was released on 2023-10-01 with total page 951 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of The Sage Handbook of Social Network Analysis builds on the success of its predecessor, offering a comprehensive overview of social network analysis produced by leading international scholars in the field. Brand new chapters provide both significant updates to topics covered in the first edition, as well as discussing cutting edge topics that have developed since, including new chapters on: · General issues such as social categories and computational social science; · Applications in contexts such as environmental policy, gender, ethnicity, cognition and social media and digital networks; · Concepts and methods such as centrality, blockmodeling, multilevel network analysis, spatial analysis, data collection, and beyond. By providing authoritative accounts of the history, theories and methodology of various disciplines and topics, the second edition of The SAGE Handbook of Social Network Analysis is designed to provide a state-of-the-art presentation of classic and contemporary views, and to lay the foundations for the further development of the area. PART 1: GENERAL ISSUES PART 2: APPLICATIONS PART 3: CONCEPTS AND METHODS

Download or read book Advances in Network Clustering and Blockmodeling written by Patrick Doreian and published by John Wiley & Sons. This book was released on 2020-02-03 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of the developments and advances in the field of network clustering and blockmodeling over the last 10 years This book offers an integrated treatment of network clustering and blockmodeling, covering all of the newest approaches and methods that have been developed over the last decade. Presented in a comprehensive manner, it offers the foundations for understanding network structures and processes, and features a wide variety of new techniques addressing issues that occur during the partitioning of networks across multiple disciplines such as community detection, blockmodeling of valued networks, role assignment, and stochastic blockmodeling. Written by a team of international experts in the field, Advances in Network Clustering and Blockmodeling offers a plethora of diverse perspectives covering topics such as: bibliometric analyses of the network clustering literature; clustering approaches to networks; label propagation for clustering; and treating missing network data before partitioning. It also examines the partitioning of signed networks, multimode networks, and linked networks. A chapter on structured networks and coarsegrained descriptions is presented, along with another on scientific coauthorship networks. The book finishes with a section covering conclusions and directions for future work. In addition, the editors provide numerous tables, figures, case studies, examples, datasets, and more. Offers a clear and insightful look at the state of the art in network clustering and blockmodeling Provides an excellent mix of mathematical rigor and practical application in a comprehensive manner Presents a suite of new methods, procedures, algorithms for partitioning networks, as well as new techniques for visualizing matrix arrays Features numerous examples throughout, enabling readers to gain a better understanding of research methods and to conduct their own research effectively Written by leading contributors in the field of spatial networks analysis Advances in Network Clustering and Blockmodeling is an ideal book for graduate and undergraduate students taking courses on network analysis or working with networks using real data. It will also benefit researchers and practitioners interested in network analysis.