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Gephi (/ˈɡɛfi/ GHEF-ee) is an open-source network analysis and visualization software package written in Java on the NetBeans platform.
The analysis highlights History and Applications as prominent areas in the source structure around Gephi.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Gephi shows recurring relationship patterns in the source. For example, Gephi → Code, Compiègne, France, Google Summer, Initially, Its, Previous, Technology, University, UTC Another extracted example is Gephi → LinkedIn InMaps, New York Times, Truthy, Twitter. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
network netbeans analysis visualization java written platform 2010 used open-source software history also developers french development website ghef-ee 2011 2012
TTTA extracted 27 structured relationships around Gephi. Examples in this analysis include Gephi → Available in → English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech, German, Romanian, Greek, Hungarian, Korean, Swedish, Ukrainian and Gephi → Developers → Mathieu Bastian, Eduardo Ramos Ibañez, Mathieu Jacomy, Cezary Bartosiak, Sébastien Heymann, Julian Bilcke, Patrick McSweeney, André Panisson, Jérémy Subtil, Helder Suzuki, Marti…. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Gephi | Available in | English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech, German, Romanian, Greek, Hungarian, Korean, Swedish, Ukrainian | 1.00 | infobox |
| Gephi | Developers | Mathieu Bastian, Eduardo Ramos Ibañez, Mathieu Jacomy, Cezary Bartosiak, Sébastien Heymann, Julian Bilcke, Patrick McSweeney, André Panisson, Jérémy Subtil, Helder Suzuki, Marti… | 1.00 | infobox |
| Gephi | License | GNU General Public License, Common Development and Distribution License | 1.00 | infobox |
| Gephi | Operating system | Linux, Windows, macOS | 1.00 | infobox |
| Gephi | Platform | NetBeans | 1.00 | infobox |
| Gephi | Release | 31 July 2008; 18 years ago (2008-07-31) | 1.00 | infobox |
| Gephi | Repository | github.com/gephi/gephi | 1.00 | infobox |
| Gephi | Size | 121.1 MB | 1.00 | infobox |
| Gephi | Stable release | 0.11.2 / 9 May 2026; 3 months ago (9 May 2026) | 1.00 | infobox |
| Gephi | Type | Visualization | 1.00 | infobox |
| Gephi | Website | gephi.org | 1.00 | infobox |
| Gephi | Written in | Java, OpenGL | 1.00 | infobox |
The concept neighborhoods around Gephi bring nearby vocabulary together. In this analysis, examples include Network, Analysis and Used. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Gephi, one of the stronger structural bridges in this analysis connects Gephi with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Gephi to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History & Applications, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Gephi · EN edition · Analysis: TopicsToTalkAbout