How to cite Gephi?

If you have found Gephi helpful in your research, please consider citing the paper published at AAAI ICWSM’09. By doing this, you contribute to the recognition of tool-building as a valuable scientific activity that has impact.

Cite Gephi

Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.

BibTex

@paper{ICWSM09154,
author = {Mathieu Bastian and Sebastien Heymann and Mathieu Jacomy},
title = {Gephi: An Open Source Software for Exploring and Manipulating Networks},
conference = {International AAAI Conference on Weblogs and Social Media},
year = {2009},
keywords = {network;network science;visualization;graph exploration;open source;free software;dynamic network;interactive interface;graph;force vector;java;OpenGL;3-D visualization;user-centric;graph layout;complex graph rendering;network analysis;webatlas},
abstract = {Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results. We present several key features of Gephi in the context of interactive exploration and interpretation of networks. It provides easy and broad access to network data and allows for spatializing, filtering, navigating, manipulating and clustering. Finally, by presenting dynamic features of Gephi, we highlight key aspects of dynamic network visualization.},
url = {http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154}
}

See other formats

Who cited Gephi? See the papers in Google Scholar here.

icwsm-logo_sm

Official paper: ICWSM 2009

This paper provides an overview of the goals and techniques used by Gephi.

Abstract

Gephi : An Open Source Software for Exploring and Manipulating Networks

Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results. We present several key features of Gephi in the context of interactive exploration and interpretation of networks. It provides easy and broad access to network data and allows for spatializing, filtering, navigating, manipulating and clustering. Finally, by presenting dynamic features of Gephi, we highlight key aspects of dynamic network visualization.

paper ICWSM 2009 Gephi Demo
pdf Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. From AAAI [PDF].

IEEE EuroVis2010

Poster: IEEE Eurovis 2010

The poster concentrates on the visualization topic and a general project presentation. It describes the visualization architecture built for the OpenGL and Preview engine.

EuroVis 2010 is the 12th annual Visualization Symposium jointly organized by the Eurographics Working Group on Data Visualization and the IEEE Visualization and Graphics Technical Committee.

Abstract

Using Computer Games Techniques for Improving Graph Viz Efficiency

Gephi is a modular and extensible open-source network visualization platform. It follows a pragmatic approach for visualization by using two different engines for two different purposes. Large scale graph drawing requires performance and interactivity, but also customization and implementation flexibility. We observed that fulfilling all aspects in a single rendering engine is technically not viable on a long-term view and propose to use different technologies. Gephi project aims to create a sustainable software and technical ecosystem, driven by a large international open-source community, who shares common interests in networks and complex systems. It focuses on visualization and manipulation, simplicity and extensibility.

Full Abstract (2 pages)
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Gephi Poster Eurovis2010

Poster: INSNA Sunbelt 2010

Social Networks and the network perspective have been recognized as relevant and important in a number of areas of inquiry. The International Sunbelt Social Network Conference is the official conference of the International Network for Social Network Analysis (INSNA).

Abstract

Gephi is a new open-source network visualization platform. It aims to create a sustainable software and technical ecosystem, driven by a large international open-source community, who shares common interests in networks and complex systems. The rendering engine can handle networks larger than 100K elements and guarantees responsiveness. Designed to make data navigation and manipulation easy, it aims to fulfill the complete chain from data importing to aesthetics refinements and interaction. Particular focus is made on the software usability and interoperability with other tools. A lot of efforts are made to facilitate the community growth, by providing tutorials, plug-ins development documentation, support and student projects. Current developments include Dynamic Network Analysis (DNA) and spigots (Emails, Twitter, Facebook …) import.

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Other publications

This wiki page contains more or less all contributions made within or in collaboration with the Gephi project. You can find here inproceedings, incollections, and articles but also Master Theses and Seminar Works.

About Network Science

Network Science is a new and emerging scientific discipline that examines the interconnections among diverse physical, informational, biological, cognitive, and social networks. This field of science seeks to discover common principles, algorithms and tools that govern network behavior. The National Research Council defines Network Science as “the organized knowledge of networks based on their study using the scientific method.” In this context, network visualization brings a complementary way to statistical analysis to discover, extract and classify new patterns in network structure and data.

Learn more: http://en.wikipedia.org/wiki/Network_science