Large groups of people can drastically change their opinion, adopt a completely unexpected trend, come out to protest on a square, adopt a certain ideology, have an amazing time at a party, or start using a certain product on mass scale. While all these social phenomena are diverse, one thing in common is that they involve information dissemination that happens in a synchronized way, evoking a certain response from the population at once.

In this workshop I will demonstrate how epidemic theories from network science can be used to study information contagion and trend/rumor propagation (so-called information cascades). We will use real examples from Facebook and Twitter, as well as Gephi software to visualise the sample data.

You will learn what groups to target when planning effective marketing campaigns, how promote your news to the top of the feed on Facebook, generate and seed trends in social networks. You will also find out how information becomes viral and what one can do in order to increase the message’s contagious potential.

The workshop will be held in English and German.

To sign up: workshopinformationepidemics-eorg.eventbrite.com

Date: 16th of February, from 6:00 PM to 8:00 PM
Place: betahaus, 19-20 Prinzessinnenstr (U8: Moritzplatz), 4th floor Arena hall

Gephi’s vision focuses on the platform and we want developers to be creative and successful. Gephi is built in a way it can be easily extended with plug-ins (layout, filters, io, preview, …) but it’s not always easy to know where to start. The bootcamp addresses this need and provide the environment and the examples to get started.

Want to create a new layout? The Grid Layout example shows how to read the graph and to change coordinates. A new filter? A new exporter? Check out the JPGExporter or the SQLite exporter examples. Below is the complete list of examples and we’ll add more soon upon requests.

Checkout the code on GitHub.

The README file contains the instructions to get the code and to run the examples.

Layout

	Grid Layout Place all nodes in a simple grid. Users can configure the size of the area and the speed.
	Sorted Grid Layout Same example as Grid Layout but users can sort nodes using an attribute column.

Filter

	Transform to Undirected Edge filter to remove mutual edges in a directed graph.
	Top nodes Keep the top K nodes using an attribute column.
	Remove Edge Crossing Example of a complex filter implementation which removes edges until no crossing occurs.

Tool

	Find with autocomplete Tool with a autocomplete text field to find any node based on labels and zoom by it.
	Add Nodes Listen to mouse clicks and adds nodes. Also adds edges if selecting other nodes.

Export

	JPG Export Vectorial export to the JPG image format. Contains a settings panel to set the width and height.
	SQLite Database Export Current graph export to a SQLite Database file. A new sub-menu is added in the Export menu and an example of a custom exporter is shown.

Preview

	Highlight Mutual Edges Colors differently mutual edges. Overwrites and extends the default edge renderer.
	Glow Renderer Adds a new renderer for node items which draws a glow effect around nodes.
	Node Z-ordering Extends the default node builder by reordering the node items by size or any number columns. Also shows how to create complex Preview UI.

Importer

Matrix Market File Importer File importer for the Matrix Market format. Large set of matrix file examples on Yifan Hu’s gallery.

Statistics

	Count Self-Loop Example of a statistics result at the global level. Simply counts the number of self-loop edges in the graph.
	Average Euclidean Distance Example of a per-node calculation. For a given node it calculates the average distance to others.

Plugins sub-menu

	Test action Simple action which displays a message and a dialog.
	Remove self loops Action which accesses the graph and removes self-loops, if any.
	Using Progress and Cancel Action which creates a long task and executes it with progress and cancel support.

Execute at startup

	When UI is ready Do something when the UI finished loading.
	Workspace select events Do something when a workspace is selected.

Processor

Initial Position Set up the nodes’ initial position always the same. It calculates a hash with all nodes so the X/Y position is randomized always in the same way.

Panels

New panel Example of a new panel plugin set up at the layout position.

If you have any questions please send an email to the gephi-plugins [at] lists.gephi.org mailing list or stop by on the forum.

In this workshop we will demonstrate a novel method for text network analysis using Gephi graph visualization software. Unlike other topic modelling methods (latent semantic network analysis, LDA) our approach takes into account the structural properties of text network in order to identify the clusters for meaning circulation and the most influential concepts within the text. You will learn how to create graph network representations of texts and perform their comparative quantitive and qualitative analysis. The method can be especially useful for quick text summarization and group sentiment profiling.

What It Can Be Used For:

– Identifying the most influential concepts and topics within a text.
– Comparing different texts together, especially what strategy a text uses to “push” a certain agenda.
– Group sentiment analysis: find the terms that unite any group together
– Quick text summary and overview (can be especially useful for studying or law text)

If you’d like to participate you can send us a short text (200 to 300 words) to info at noduslabs dot com describing your interests and current occupations. We will create text graphs both for participants and the whole group and see how they relate to one another (see the image attached). This may also be useful for you to meet other like-minded individuals at betahaus or find the people who could complement your cognitive map with their knowledge.

To sign up: workshopnoduslabs1.eventbrite.com

We highly recommend you to bring your laptop with you and pre-install Gephi graph visualization software on your computer (works on Mac, PC, Linux).

The plugin let you visualize a graph stored in a Neo4j database and play with it. Features include full import, traversal, filter, export and lazy loading.

Neo4j Integration into Gephi from gephi on Vimeo.

The plug-in is officially supported by the Neo4j team and is open to contribution! The code is hosted on GitHub.

If you have suggestions please send them our way, we would love to hear your feedback! The forum is the best place for that.

We hope you’ll find GitHub faster and easier to use than Launchpad. The team is already appreciating how easy it is to report issues and work together on the code. GitHub has more than a million users and will make the project more visible and ease external contributions.

Technically, we migrated our branches from Bazaar to Git (thanks to git-bzr) so the history is entirely kept. We also moved all our bugs with a simple script. We are still working on the details. If you see something wrong or missing on GitHub, please contact us or create an issue on GitHub. If you had some branches on Launchpad, you can find them on the GitHub repository. Let us know if you have questions. Contributors simply fork the repository and get started. We updated the documentation on the wiki. Consult the Developer Handbook.

Checkout code

Run
git clone git://github.com/gephi/gephi.git

Report issues

Simply go to the Issues tab.

Build in one step

Simply run ant at the root of the repository to build Gephi. The executable are located in the dist folder.

We made some improvements on the building process. Previously, Netbeans was required to build Gephi. We now integrates the platform directly in the source code so it’s not necessary anymore. It’s literally a one step process.

Please let us know your feedbacks and questions as usual on the forum.

It includes all features and bugfixes the 0.8 beta version has. Check out the Release Notes

Demos available on the Toolkit Portal have been adapted when necessary and tested. If you are interested in using plug-ins from the Toolkit, checkout How to use plug-ins with the Toolkit.

One of the exciting new feature released in the 0.8 beta is the new Preview. Because it has been completely rewritten with a much simpler and powerful API it’s now possible to reuse the Processing-based applet in other applications. You can now reproduce the zoom-and-pan experience in Gephi’s Preview tab in other Java applications easily. Checkout this demo to learn more.

Links you may be interested:

• Gephi Toolkit Tutorial (updated with new Ranking and Preview)
• Tips to use the Gephi Toolkit with other JVM languages

I get scratched with this statement made by Ben Fry in the book ‘Visualizing Data‘ (2008). Although I have a great respect for Ben Fry’s work and his position may have evolve since then, I want to moderate this statement so that data explorers like danbri can make their own opinion.

Ben Fry in ‘Visualizing Data‘:

Graphs can be a powerful way to represent relationships between data, but they are also a very abstract concept, which means that they run the danger of meaning something only to the creator of the graph. Often, simply showing the structure of the data says very little about what it actually means, even though it’s a perfectly accurate means of representing the data. Everything looks like a graph, but almost nothing should ever be drawn as one.

There is a tendency when using graphs to become smitten with one’s own data. Even though a graph of a few hundred nodes quickly becomes unreadable, it is often satisfying for the creator because the resulting figure is elegant and complex and may be subjectively beautiful, and the notion that the creator’s data is “complex” fits just fine with the creator’s own interpretation of it. Graphs have a tendency of making a data set look sophisticated and important, without having solved the problem of enlightening the viewer.

I totally disagree. Look at this simple plot:

Can anyone tell me how, simply showing this plot, one is enlightened if I don’t tell how it was done, and what is interesting to look at? It however appears very simple: only one curve, something that you are used to see since the time you discovered this kind of drawing in primary school. And even if I give some insights on how I made it and the context of the work, I’m still, as the creator, the only one able to deeply understand the information that can be extracted because I know the process that built the underlying data. To criticize my conclusions, you will need to learn as much as I did and you will need to get the same data and apply the same manipulations. Depending on the curation, reformatting, filtering or whatever the algorithms you used to capture, extract and use some data, each action has an impact on the meaning carried on by the data. Graph visualization is no exception, and is like any plot except that you can’t hide the structural complexity without explicit filtering.

Let’s enumerate all the dimensions used in a graph visualization: x+y coordinates, size of nodes, color of nodes, thickness of edges. Well, it is not easy to read on 5 dimensions. But is the “simple” plot a better deal? You have x+y coordinates, so 2 dimensions only (we might also have used colors and dot sizes as well, and get 4 dimensions). So you might think that you and your readers can interpret it easily and reliably. You are all wrong because of the hidden dimension: scaling.

Here you see a plot in a log-lin scale, that mean the y-axis is in a logarithm scale, while the x-axis is in a normal scale. I found this visual pattern interesting on these data because of my research question, because I understand the meaning on the process that made them, and because I found it in this particular scale. Plotted in lin-lin scale, I can find less information. Or maybe should I use a cumulative function to plot my data? Maybe an inverse cumulative? Etc. An exploration of both data and projection techniques is required.

By doing one projection, I focus on something very particular on the data, and I still need other plots and statistical tests a) to decide whether it supports an hypothesis I have in mind, or b) if I can find something new, something unexpected. The distortion of vision is therefore at the same time an issue and a tool to better dig inside the data. I could also make very wrong conclusions, even on analyzing this simple drawing, so why external readers should be more protected this way? There is a balance to find between a drawing that looks simple to read so conclusions appear obvious (even if they are not and you might be wrong), and the opposite one that looks too complex to read so little conclusions will be made, if any. Hence this is a fallacy to argue that graphs are meaningful only for their creator, because it is the case for any plot taken solely, and it is a hard job to enter into the work of somebody else anyway.

So graph visualization is not naturally worse compared to any data drawing: we just don’t teach how to read them in primary school. Do you remember the first time you saw a plot? I guess you find it really abstract. Most of the people don’t really know what to look at on a graph, and produce visualizations that don’t show something in particular. I personally think that it is a good thing, because put in context graph visualization is very young compared to other data drawings, and a language of networks that combine layout algorithms and visual variables is still in the making. Moreover, after meeting and discussing with people publishing such visuals, it seems that they already use it in a pragmatic way: by showing their complexity, graphs communicate to the reader that a) data might contain interesting information (“so please, read until the end!”), b) they made things and propose some findings but it was hard and many other things could be done (“hey, let’s try by yourself!”). It is useless to discover the secrets of the universe if nobody listen to you. Before enlightening the viewer, one should attract the viewer enough so that he/she will take the time to read, and graphs are useful for that need.

But drawing graphs as graphs is not only useful to communicate. Their primary use for researchers is exploratory analysis when the study is not focused on the sole structure of the data, but when elements in context matter because you have a prior knowledge on them, and your questions are related to another perspectives (say, sociology). I take the example of our work at Sciences-Po, where we teach the mapping of controversies to students that will become the future decision makers of companies or public policies. Part of the controversies in the public space are expressed on the Web. The dynamics of the discussions and the hyperlink structure of the Web makes this field particularly hard to investigate. We successfully use graph visualization of websites to help the students to orientate in this space, to assist and justify the classification of websites, and to assert the position of the actors of a controversy. This is just one case among others where there is currently no viable alternative to graph drawing and it’s synoptical property (see the whole without reduction of data).

Finally, the different usages of graph drawing are growing as it becomes mainstream and more people are acculturated. I trust on the people to innovate and progressively learn how to read and extract information. Just practice.

The team will now start developing the 0.9 version of Gephi (please consider joining us!) and integrate the latest Google Summer of Code projects, including a new timeline. We are also willing to help as much as possible plug-ins developers to get things done and improve documentation. We want to leverage the new Preview and will help newcomers to get started.

Because it’s a major release, changes are not deployed through the AutoUpdate, you need to download and install the new version. Plug-ins also need to be checked for compatibility. They will reappear on the Plugin Center in the coming days, as they are verified. Thanks for your patience.

Consult the release notes and the new Javadoc for more information.

Features highlight

	Dynamic Ranking Ranking now works with dynamic networks and it’s easy! When manipulating a dynamic network with the Timeline simply enable the ‘Auto Apply’ and the color/size is updated in real-time. To import a dynamic node size simply import a regular dynamic column in your GEXF and select it in Ranking like before.
	PNG Export A new powerful PNG export has been added to the existing PDF and SVG export. One can create high-resolution network images with all the customization available in Preview. You can even create transparent background images!
	New Preview Major effort to completely rewrite the Preview module in a modular way. One can now create plug-ins for Preview! The new Preview includes new opacity options, a text outline, radius (customize edge start/end points) and a simplified list of properties.
	Dynamic Metrics New dynamic metrics in the Statistics module: Dynamic Degree, Dynamic Node Count, Dynamic Edge Count and Dynamic Clustering Coefficient. Dynamic metrics are executed on a dynamic network and allow to analyze how network properties evolve over time.

New And Noteworthy

* Data Lab node merging
* ForceAtlas2 layout algorithm, with multi-thread option
* Node and Edge transparency in Preview
* Edge labels on curved edges in Preview
* Text outline now in Preview
* Database importer now supports time columns (start & end)
* DL Export (Thanks to Taras Klaskovsky)
* GML Export (Thanks to Taras Klaskovsky)
* NET Export (Thanks to Daniel Bernardes)
* K-core filter
* Inter and Intra partition filter
* Now supports SQLite databases
* Display the number of layout iterations in status bar when ended
* Recent Palette in Ranking
* Weighted degree now also for directed graphs

New localization (Go to Tools > Languages)

* Portuguese (Brazilian) (Thanks to Célio Faria Jr)
* Japanese (Thanks to Siro Kida and Koji Chono)

Performance

* Memory starvation manager, warns the user before running out of memory
* Less memory usage with attributes

Bug fixes

* Timeline need more precision when dealing with dates (bug 521937)
* Exception on range slider (bug 541808)
* Inconsistent label data from Overview to Preview (bug 660204)
* Statistics: sub-optimal modularity (bug 727701)
* Timeline cann’t drag if the two sliders moved to the left (bug 745476)
* Missing Polish characters when exporting to pdf (bug 746740)
* Edge selection color is not correct on OSX (bug 752300)
* Workspace name truncated, hard to read (bug 758578)
* Average degree cannot be switched to directed / undirected (bug 760454)
* Window->Favorites appears in 0.8 alpha (bug 764494)
* Disable ‘directed’ on metric settings if the graph is undirected (bug 771318)
* Timeline does not work (exception) (bug 774455)
* Layout properties can’t be saved in a language and loaded in another language (bug 783637)
* Preview: edge label not shown (bug 783868)
* Possible memory leak on Dynamic Range Filter (bug 784606)
* Edge attributes not saved in .gephi project file (bug 785268)
* Data Lab: Exception when selecting only one column for merging (bug 785269)
* Data Lab Import Spreadsheet should not ignore parallel edges (bug 785635)
* Data Laboratory: wrong edge type created (mutual instead of directed) (bug 787401)
* Data Lab: impossible to edit time intervals in a date format (bug 793163)
* Spelling of Proportionnal (bug 794358)
* Graphics errors when JOGL installed as a JRE/JDK extension (bug 799545)
* NPE if source/target is empty in GEXF import (bug 799574)
* Toolkit can’t open .gephi files (bug 802101)
* Resizing edge sizes changes edge weight values (bug 803763)
* Preview does not use node label settings from overview tab (bug 805763)
* Data Lab ‘Import Spreadsheet’ dialogue should accept other file types than .csv (bug 806798)
* Edge weights not imported from CSV matrix (bug 808078)
* Preview tab: no option to switch off node borders? (bug 808606)
* Gephi runs out of memory without warning the user (bug 811373)
* Counter-intuitive filename in Data export dialog (bug 814178)
* NullPointerException when creating newProjects too quickly (bug 817170)
* Nodes and edges Id attribute dictionary is not properly created when loading a .gephi file (bug 818181)
* Database driver doesn’t persist in Edge List Database import UI (bug 822316)
* NodeEqualNumberFilter does not work (bug 823038)
* Gephi does not build on JDK 7 (bug 823543)
* SVG node, edge export should include relevant node IDs as classes (bug 827706)
* Import Spreadsheet: need to trim column names (bug 829956)
* Layout list not sorted by name (bug 830149)
* In/Out degree metric is computed on the main graph instead of the visible graph (bug 830752)
* Layout is not giving the algorithm’s number of iterations (bug 831782)
* Banner height issues, need a fixed height (bug 834400)
* NPE when running ClusteringCoefficient on a filtered graph (bug 852799)
* Missing node properties from dot file (bug 855410)
* ‘The value column doesn’t exist’ error when opening a gephi file (bug 857595)
* Import fails for NET (Pajek) file with position/color data (bug 860825)
* GEXF export referes to v1.1 schema, should be v1.2 schema (bug 864484)

New Plug-ins documentation

Checkout the documentation for the newly created Preview module: HowTo write a Preview Renderer. Learn also how to extend the Data Laboratory features in a new tutorial.

New license

Gephi is now released in the dual license CDDL + GNU GPLv3. We abandon the GNU AGPL to offer new opportunities to reuse and integrate parts of Gephi in a full Open Source way. The dual license system means the possibility to choose to apply either the CDDL or the GNU GPLv3 when Gephi source code is integrated to a derivative work. When modified, original files of Gephi should always be published publicly so that the community benefit from the improvements. However, the CDDL license does not require to publish the whole work, so you can build commercial applications for free using Gephi source code!
The CDDL is a license created by Sun and approved by the Open Source Initiative. It is business-friendly. Read the Legal FAQs to learn more, and ask questions on the forum.

Contribute

It’s fun to contribute to an open-source project! Contribute whatever the time you can give: few minutes to  report a bug, some hours to fix one or to translate the user interface or more to create a plug-in. If you’re a student and looking for cool and challenging semester projects check out the Gephi Student Program or contact us.

Do Gephi technologies matter for your research or business? You can support us by donating to the Gephi Consortium, or becoming a member to have an impact on our roadmap.

Feel free to reach to us if you are willing to organize events (meetups, workshops, hackathon, etc.), we will support them.

This is an announcement for the first Gephi Plugins Developers Workshop October 6, 2011 in Mountain View, California. Come and learn how to write your first Gephi plugin and ask questions. The workshop is organized by Mathieu Bastian, Gephi Architect and will be gratefully hosted by IMVU.

Gephi is a modular software and can be extended with plug-ins. Plug-ins can add new features like layout, filters, metrics, data sources, etc. or modify existing features. Gephi is written in Java so anything that can be used in Java can be packaged as a Gephi plug-in! Visit the Plugins Portal on the wiki and follow the tutorials to get started.

The workshop will start with a presentation of Gephi’s architecture and the different types of plugins that can be written with examples. Details about Gephi’s APIs, code examples and best practices will be presented in an interactive “live coding” way. The Gephi Toolkit will also be covered in details. The second part of the workshop will be dedicated to help individuals with their projects and answer questions.

Some of the best projects using or extending Gephi are developed in the Silicon Valley and we are looking forward helping the developer community. Please don’t hesitate to send us your ideas to maximize efficiency.

RSVP here