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 2023-01-05 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on the theory and applications of network science is aimed at beginning graduate students in statistics, data science, computer science, machine learning, and mathematics, as well as advanced students in business, computational biology, physics, social science, and engineering working with large, complex relational data sets. It provides an exciting array of analysis tools, including probability models, graph theory, and computational algorithms, exposing students to ways of thinking about types of data that are different from typical statistical data. Concepts are demonstrated in the context of real applications, such as relationships between financial institutions, between genes or proteins, between neurons in the brain, and between terrorist groups. Methods and models described in detail include random graph models, percolation processes, methods for sampling from huge networks, network partitioning, and community detection. In addition to static networks the book introduces dynamic networks such as epidemics, where time is an important component.

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 Report of a Working Group on Beta and World Beta Network written by and published by Bioversity International. This book was released on with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Working Your Network Vol 1 written by Mark Champion and published by Working Your Network. This book was released on 2006-12 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Champion shares his experience and innovative business and technology philosophies, which can enable readers to think intelligently about their business technology environment and maximize their company's market share through large-scale thinking that keeps in mind the needs of any sized business. (Computer Books)

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 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 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 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 Network Data Analytics written by K. G. Srinivasa and published by Springer. This book was released on 2018-04-26 with total page 398 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 Report of a working group on beta and the World Beta Network third joint meeting 8 11 March 2006 Puerto de la Cruz Tenerife Spain written by and published by Bioversity International. This book was released on 2009 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Working Around Disruptions of Network Infrastructures written by Amro Al-Akkad and published by Springer. This book was released on 2016-02-22 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: As in disasters the availability of information and communication technology services can be severely disrupted, the author explores challenges and opportunities to work around such disruptions. He therefore empirically analyzes how people in disasters use remnants of technology to still communicate their needs. Based on this, he suggests quality attributes whose implementation can support the resilience in technology. To exemplify this he develops iteratively two mobile ad-hoc systems and explores their feasibility and implications for emergency response under close-to-real conditions. Compared to the state of the art both systems are independent from preexisting network infrastructure and run on off-the-shelf smartphones.

Download or read book Social Network Analysis written by Mohammad Gouse Galety and published by John Wiley & Sons. This book was released on 2022-04-28 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Network Data Mining And Analysis written by Gao Ming and published by World Scientific. This book was released on 2018-09-27 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online social networking sites like Facebook, LinkedIn, and Twitter, offer millions of members the opportunity to befriend one another, send messages to each other, and post content on the site — actions which generate mind-boggling amounts of data every day.To make sense of the massive data from these sites, we resort to social media mining to answer questions like the following:Social media shatters the boundaries between the real world and the virtual world. We can now integrate social theories with computational methods to study how individuals interact with each other and how social communities form in bipartite and signed networks. The uniqueness of social media data calls for novel data mining techniques that can effectively handle user generated content with rich social relations. The study and development of these new techniques are under the purview of social media mining, an emerging discipline under the umbrella of data mining. Social Media Mining is the process of representing, analyzing, and extracting actionable patterns from social media data.

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 Networking Essentials written by Jeffrey S. Beasley and published by Pearson Education. This book was released on 2012-03-01 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly updated to reflect CompTIA’s Network+ N10-005 exam, Networking Essentials, Third Edition, is a practical, up-to-date, and hands-on guide to the basics of networking. Written from the viewpoint of a working network administrator, it requires absolutely no experience with either network concepts or day-to-day network management. Networking Essentials, Third Edition, includes expanded coverage of cabling, a new introduction to IPv6, and new chapters on basic switch configuration and troubleshooting. Its wireless and security chapters now focus strictly on introductory material, and you will also find up-to-date introductions to twisted-pair and fiber optic cabling, TCP/IP protocols, Internet and LAN interconnections, and basic network problem identification and resolution. Clear goals are outlined for each chapter, and every concept is introduced in easy to understand language that explains how and why networking technologies are used. Each chapter is packed with real-world examples and practical exercises that reinforce all concepts and guide you through using them to configure, analyze, and fix networks. Key Pedagogical Features NET-CHALLENGE SIMULATION SOFTWARE provides hands-on experience with entering router and switch commands, setting up functions, and configuring interfaces and protocols WIRESHARK NETWORK PROTOCOL ANALYZER presents techniques and examples of data traffic analysis throughout PROVEN TOOLS FOR MORE EFFECTIVE LEARNING & NETWORK+ PREP, including chapter outlines, summaries, and Network+ objectives WORKING EXAMPLES IN EVERY CHAPTER to reinforce key concepts and promote mastery KEY TERM DEFINITIONS, LISTINGS & EXTENSIVE GLOSSARY to help you master the language of networking QUESTIONS, PROBLEMS, AND CRITICAL THINKING QUESTIONS to help you deepen your understanding