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Beschreibung
Produce advanced network graphs in Gephi and gain valuable insights into your network datasets
Key Features
Build sophisticated interactive network graphs using advanced Gephi layout features
Master Gephi statistical and filtering techniques to easily navigate through even the densest network graphs
An easy-to-follow guide introducing you to Gephi's advanced features, with step-by-step instructions and lots of examples
Book Description
Mastering Gephi Network Visualization will take you through an overview of Gephi and network behavior, followed by detailed chapters addressing layouts, filtering, graph statistics, dynamic graphs, and more. You will begin with a concise overview of working with the Gephi interface. You will then see how to create your own graphs and understand the graph layouts to arrange a sample dataset. You will understand the theory behind Dynamic Network Analysis, followed by sample applications on how Gephi can be used to model these networks. You will also learn about the plugins that are most critical for network analysis and graph creation. Finally, you will put together all the previously learned concepts and gain insight on the future state of network graph analysis.
After reading this book and following the examples provided, you will have the confidence and expertise to create your own compelling graphs.
What you will learn
Familiarize yourself with the Gephi interface
Understand the plugins that are most critical for network analysis and graph creation
Assess your own network graph needs
Examine key network behaviors such as contagion, diffusion, and clustering
Effectively display a sample dataset using your own graphs
Identify and analyze network patterns
Use Gephi's powerful filtering capabilities to improve your graphs
Create dynamic graphs with time-based network data
Export your graphs for use beyond Gephi
Key Features
Build sophisticated interactive network graphs using advanced Gephi layout features
Master Gephi statistical and filtering techniques to easily navigate through even the densest network graphs
An easy-to-follow guide introducing you to Gephi's advanced features, with step-by-step instructions and lots of examples
Book Description
Mastering Gephi Network Visualization will take you through an overview of Gephi and network behavior, followed by detailed chapters addressing layouts, filtering, graph statistics, dynamic graphs, and more. You will begin with a concise overview of working with the Gephi interface. You will then see how to create your own graphs and understand the graph layouts to arrange a sample dataset. You will understand the theory behind Dynamic Network Analysis, followed by sample applications on how Gephi can be used to model these networks. You will also learn about the plugins that are most critical for network analysis and graph creation. Finally, you will put together all the previously learned concepts and gain insight on the future state of network graph analysis.
After reading this book and following the examples provided, you will have the confidence and expertise to create your own compelling graphs.
What you will learn
Familiarize yourself with the Gephi interface
Understand the plugins that are most critical for network analysis and graph creation
Assess your own network graph needs
Examine key network behaviors such as contagion, diffusion, and clustering
Effectively display a sample dataset using your own graphs
Identify and analyze network patterns
Use Gephi's powerful filtering capabilities to improve your graphs
Create dynamic graphs with time-based network data
Export your graphs for use beyond Gephi
Produce advanced network graphs in Gephi and gain valuable insights into your network datasets
Key Features
Build sophisticated interactive network graphs using advanced Gephi layout features
Master Gephi statistical and filtering techniques to easily navigate through even the densest network graphs
An easy-to-follow guide introducing you to Gephi's advanced features, with step-by-step instructions and lots of examples
Book Description
Mastering Gephi Network Visualization will take you through an overview of Gephi and network behavior, followed by detailed chapters addressing layouts, filtering, graph statistics, dynamic graphs, and more. You will begin with a concise overview of working with the Gephi interface. You will then see how to create your own graphs and understand the graph layouts to arrange a sample dataset. You will understand the theory behind Dynamic Network Analysis, followed by sample applications on how Gephi can be used to model these networks. You will also learn about the plugins that are most critical for network analysis and graph creation. Finally, you will put together all the previously learned concepts and gain insight on the future state of network graph analysis.
After reading this book and following the examples provided, you will have the confidence and expertise to create your own compelling graphs.
What you will learn
Familiarize yourself with the Gephi interface
Understand the plugins that are most critical for network analysis and graph creation
Assess your own network graph needs
Examine key network behaviors such as contagion, diffusion, and clustering
Effectively display a sample dataset using your own graphs
Identify and analyze network patterns
Use Gephi's powerful filtering capabilities to improve your graphs
Create dynamic graphs with time-based network data
Export your graphs for use beyond Gephi
Key Features
Build sophisticated interactive network graphs using advanced Gephi layout features
Master Gephi statistical and filtering techniques to easily navigate through even the densest network graphs
An easy-to-follow guide introducing you to Gephi's advanced features, with step-by-step instructions and lots of examples
Book Description
Mastering Gephi Network Visualization will take you through an overview of Gephi and network behavior, followed by detailed chapters addressing layouts, filtering, graph statistics, dynamic graphs, and more. You will begin with a concise overview of working with the Gephi interface. You will then see how to create your own graphs and understand the graph layouts to arrange a sample dataset. You will understand the theory behind Dynamic Network Analysis, followed by sample applications on how Gephi can be used to model these networks. You will also learn about the plugins that are most critical for network analysis and graph creation. Finally, you will put together all the previously learned concepts and gain insight on the future state of network graph analysis.
After reading this book and following the examples provided, you will have the confidence and expertise to create your own compelling graphs.
What you will learn
Familiarize yourself with the Gephi interface
Understand the plugins that are most critical for network analysis and graph creation
Assess your own network graph needs
Examine key network behaviors such as contagion, diffusion, and clustering
Effectively display a sample dataset using your own graphs
Identify and analyze network patterns
Use Gephi's powerful filtering capabilities to improve your graphs
Create dynamic graphs with time-based network data
Export your graphs for use beyond Gephi
Über den Autor
Ken Cherven is a Detroit-based data visualization and open source enthusiast, with 20 years of experience working with data and visualization tools. In addition to Gephi, he has worked with a variety of open source tools, including MySQL, SpagoBI, JasperServer, D3, Protovis, Omeka, QGIS, Leaflet, and Exhibit. He also has considerable experience using corporate software tools from Microsoft, Cognos, Tableau, and Oracle. An automotive analyst and visualizer by day, he spends much of his personal time turning baseball data into web-based visualizations housed on his website, [...] He has previously authored Network Graph Analysis and Visualization with Gephi, Packt Publishing, as well as a self-published book, MLB Pennant Races, 1901-1968: A Visual Analysis of Baseball's Pennant Races, Visual-Baseball Press. His current areas of interest include visual dashboards, interactive networks, and anything involving geographic information.
Details
Erscheinungsjahr: | 2015 |
---|---|
Fachbereich: | Datenkommunikation, Netze & Mailboxen |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
ISBN-13: | 9781783987344 |
ISBN-10: | 1783987340 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Cherven, Ken |
Hersteller: | Packt Publishing |
Maße: | 235 x 191 x 21 mm |
Von/Mit: | Ken Cherven |
Erscheinungsdatum: | 02.02.2015 |
Gewicht: | 0,705 kg |
Über den Autor
Ken Cherven is a Detroit-based data visualization and open source enthusiast, with 20 years of experience working with data and visualization tools. In addition to Gephi, he has worked with a variety of open source tools, including MySQL, SpagoBI, JasperServer, D3, Protovis, Omeka, QGIS, Leaflet, and Exhibit. He also has considerable experience using corporate software tools from Microsoft, Cognos, Tableau, and Oracle. An automotive analyst and visualizer by day, he spends much of his personal time turning baseball data into web-based visualizations housed on his website, [...] He has previously authored Network Graph Analysis and Visualization with Gephi, Packt Publishing, as well as a self-published book, MLB Pennant Races, 1901-1968: A Visual Analysis of Baseball's Pennant Races, Visual-Baseball Press. His current areas of interest include visual dashboards, interactive networks, and anything involving geographic information.
Details
Erscheinungsjahr: | 2015 |
---|---|
Fachbereich: | Datenkommunikation, Netze & Mailboxen |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
ISBN-13: | 9781783987344 |
ISBN-10: | 1783987340 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Cherven, Ken |
Hersteller: | Packt Publishing |
Maße: | 235 x 191 x 21 mm |
Von/Mit: | Ken Cherven |
Erscheinungsdatum: | 02.02.2015 |
Gewicht: | 0,705 kg |
Warnhinweis