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Gephi Cookbook

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  • Install and configure Gephi on your system and understand its various features
  • Perform basic manipulation and exploration tasks on graphs
  • Understand various layout algorithms present by default in Gephi and the principles behind them
  • Explore the properties of graphical networks using numerous filters and statistical metrics available in Gephi
  • Import graph data from different sources and manipulate it directly in tabular formats
  • Use real-world datasets to better understand network analysis

Gephi is an open source, user-friendly network visualization and analysis tool that provides numerous powerful features, making it easy for novices to get to grips with graph analysis quickly.

This book is your one-stop guide to learning Gephi's interactive networking and visualization, alongside the graph theory concepts that drive them. Each recipe walks you through a task and explains why and how it works. Starting with installing Gephi, you will learn how to begin analyzing a graph using Gephi's various features. You will discover how to make informed decisions using layout algorithms and filters, and perform statistical analysis with real-world datasets. This guide is an invaluable resource if you would like to plunge into the network analysis domain without having to learn how to code.

  • Design and explore graphical networks using a wide range of Gephi features
  • Analyze the structure and properties of graphical networks without having to write any code
  • Learn to optimize the Gephi plugins for efficient data visualization
Page Count 296
Course Length 8 hours 52 minutes
Date Of Publication 26 May 2015
Exploring the Web and Internet domain – EuroSiS Web mapping study
Exploring the Web and Internet domain – the Internet dataset
Exploring social networks – Zachary's karate club dataset
Exploring social networks – Twitter's mentions and retweets dataset
Exploring biological networks – the C. Elegans neural network dataset
Exploring biological networks – the yeast dataset
Exploring the infrastructure domain – the airlines dataset
Importing data from MySQL databases
Importing data from Neo4j databases
Importing data via NodeXL


Devangana Khokhar

Devangana Khokhar is a consultant at ThoughtWorks Inc., working on a range of exciting projects, primarily in the data science and analytics domain and is currently based out of Bengaluru. She has more than 4 years of experience in data analytics, social networks analysis, machine learning, and information retrieval. She is also the director of Women Who Code's Bangalore chapter, a nonprofit organization focused on bringing more women into the field of technology. She holds a master's degree in theoretical computer science and has specialized in social network analysis from PSG College of Technology, Coimbatore. During her postgraduate study, she was intrigued by social networks and machine learning, and she has been in love with data science and analytics since then. Devangana has also been one of the reviewers for R Graphs Cookbook Second Edition, Jaynal Abedin and Hrishi V. Mittal, Packt Publishing.

She is passionate about spreading the message of educational equality and is an advocate of women's right to education and equal stature in the tech industry. She also takes an interest in cooking and reading books, mostly in the realm of nonfiction. She is a Twitter addict and very often shares resources that she finds interesting or useful in her pursuit of getting better at data science. She tweets at http://www.twitter.com/DevanganaK. You can also get in touch with her on LinkedIn at in.linkedin.com/in/devangana.