Network Graph Analysis And Visualization With Gephi


Network Graph Analysis And Visualization With Gephi
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Network Graph Analysis And Visualization With Gephi


Network Graph Analysis And Visualization With Gephi
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Author : Ken Cherven
language : en
Publisher: Packt Pub Limited
Release Date : 2013

Network Graph Analysis And Visualization With Gephi written by Ken Cherven and has been published by Packt Pub Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with COMPUTERS categories.


A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.



Network Graph Analysis And Visualization With Gephi


Network Graph Analysis And Visualization With Gephi
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Author : Ken Cherven
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-09-24

Network Graph Analysis And Visualization With Gephi written by Ken Cherven and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-24 with Computers categories.


A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.



Mastering Gephi Network Visualization


Mastering Gephi Network Visualization
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Author : Ken Cherven
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-01-28

Mastering Gephi Network Visualization written by Ken Cherven and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-28 with Computers categories.


This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful.



Gephi Cookbook


Gephi Cookbook
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Author : Devangana Khokhar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-05-27

Gephi Cookbook written by Devangana Khokhar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-27 with Computers categories.


If you want to learn network analysis and visualization along with graph concepts from scratch, then this book is for you. This is ideal for those of you with little or no understanding of Gephi and this domain, but will also be beneficial for those interested in expanding their knowledge and experience.



Graph Analysis And Visualization


Graph Analysis And Visualization
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Author : Richard Brath
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-30

Graph Analysis And Visualization written by Richard Brath and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-30 with Computers categories.


Wring more out of the data with a scientific approach toanalysis Graph Analysis and Visualization brings graph theory outof the lab and into the real world. Using sophisticated methods andtools that span analysis functions, this guide shows you how toexploit graph and network analytic techniques to enable thediscovery of new business insights and opportunities. Published infull color, the book describes the process of creating powerfulvisualizations using a rich and engaging set of examples fromsports, finance, marketing, security, social media, and more. Youwill find practical guidance toward pattern identification andusing various data sources, including Big Data, plus clearinstruction on the use of software and programming. The companionwebsite offers data sets, full code examples in Python, and linksto all the tools covered in the book. Science has already reaped the benefit of network and graphtheory, which has powered breakthroughs in physics, economics,genetics, and more. This book brings those proven techniques intothe world of business, finance, strategy, and design, helpingextract more information from data and better communicate theresults to decision-makers. Study graphical examples of networks using clear and insightfulvisualizations Analyze specifically-curated, easy-to-use data sets fromvarious industries Learn the software tools and programming languages that extractinsights from data Code examples using the popular Python programminglanguage There is a tremendous body of scientific work on network andgraph theory, but very little of it directly applies to analystfunctions outside of the core sciences – until now. Writtenfor those seeking empirically based, systematic analysis methodsand powerful tools that apply outside the lab, Graph Analysisand Visualization is a thorough, authoritative resource.



Network Analysis And Visualization In R


Network Analysis And Visualization In R
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Author : Alboukadel Kassambara
language : en
Publisher: STHDA
Release Date : 2017-11-26

Network Analysis And Visualization In R written by Alboukadel Kassambara and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-26 with categories.


Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.



Complex Network Analysis In Python


Complex Network Analysis In Python
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Author : Dmitry Zinoviev
language : en
Publisher: Pragmatic Bookshelf
Release Date : 2018-01-19

Complex Network Analysis In Python written by Dmitry Zinoviev and has been published by Pragmatic Bookshelf this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-19 with Computers categories.


Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Convert almost any real-world data into a complex network--such as recommendations on co-using cosmetic products, muddy hedge fund connections, and online friendships. Analyze and visualize the network, and make business decisions based on your analysis. If you're a curious Python programmer, a data scientist, or a CNA specialist interested in mechanizing mundane tasks, you'll increase your productivity exponentially. Complex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience. Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive--such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study of networkx functions and techniques, and concludes with case studies from various fields, including social networking, anthropology, marketing, and sports analytics. Combine your CNA and Python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer. What You Need: You will need a Python 3.x installation with the following additional modules: Pandas (>=0.18), NumPy (>=1.10), matplotlib (>=1.5), networkx (>=1.11), python-louvain (>=0.5), NetworKit (>=3.6), and generalizesimilarity. We recommend using the Anaconda distribution that comes with all these modules, except for python-louvain, NetworKit, and generalizedsimilarity, and works on all major modern operating systems.



Visual Complexity


Visual Complexity
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Author : Manuel Lima
language : en
Publisher: Princeton Architectural Press
Release Date : 2013-09-10

Visual Complexity written by Manuel Lima and has been published by Princeton Architectural Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-10 with Design categories.


Manuel Lima's smash hit Visual Complexity is now available in paperback. This groundbreaking 2011 book—the first to combine a thorough history of information visualization with a detailed look at today's most innovative applications—clearly illustrates why making meaningful connections inside complex data networks has emerged as one of the biggest challenges in twenty-first-century design. From diagramming networks of friends on Facebook to depicting interactions among proteins in a human cell, Visual Complexity presents one hundred of the most interesting examples of informationvisualization by the field's leading practitioners.



Visualizing Data


Visualizing Data
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Author : Ben Fry
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2008

Visualizing Data written by Ben Fry and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.


Provides information on the methods of visualizing data on the Web, along with example projects and code.



Statistical Analysis Of Network Data With R


Statistical Analysis Of Network Data With R
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Author : Eric D. Kolaczyk
language : en
Publisher: Springer
Release Date : 2014-05-22

Statistical Analysis Of Network Data With R written by Eric D. Kolaczyk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-22 with Computers categories.


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).