Extension:Collaboration Diagram

Purpose
CollaborationDiagram extension allows one to rendering and visualize bipartite graph of any article and its editors, editors and set of articles, the articles and editors of any category. It uses the free program GraphViz and GraphVizExtension for creating the and rendering bipartite graphs.

Dependencies

 * GraphViz
 * Extension:GraphViz

Usage
Here are examples of using the collaborationdia tag.

Diagram for one page




Diagram for the set of pages




Diagram for all pages in category


Using a different layout algorithm
As of version 0.1 you can use other graphviz layout algorithms, e.g. to get something like this:

Change default.dot

Special Page and tab
Go to ?title=Special:CollaborationDiagram&page= and you'll see collaboration diagram for the page Your_pagename. Alternatively you can click on the tab collaborationdiagram that located near the history tab.



Skin support
In our terminology skin is a header of generated graphviz code. The default skin is default.dot located in the Collaboration Diagram extension folder. You can write your own skin, put it in the extension folder and set $wgCollaborationDiagramSkinFilename to the skin filename in LocalSettings.php:

Download instructions
Stable

Current stable release is available from here

From svn

Version in svn typically has more features but it could be buggy. If you are strong use it! svn export http://collaborationgraph.googlecode.com/svn/trunk/ collaborationgraph-read-only

Installation
To install this extension, download it and add the following to LocalSettings.php:

Further work
Currently the extension is in active development. It's planned to make a huge refactor and the added support for the variety of viewing options. See project tracker for gory details.

Theory
From: Bipartite Networks of Wikipedias Articles and Authors: a Meso-level Approach A bipartite network is a graph G = (U, V, E) whose vertices (or `nodes') can be divided into two disjoint sets U and V such that every edge (or `link') E connects a vertex in U to a vertex in V; that is, U and V are independent sets.

When we consider articles in Wikipedia and their editors, a bipartite network is a convenient representation: U is the set of editors and V is the set of articles in Wikipedia. The bipartite network formalism is ideal for studying collaboration, because the network structure encodes knowledge about which articles editors have edited together. By studying the clusters (or `modules') in the bipartite network, we are able to discover clustering of editors and articles and smaller patterns of collaboration. These dense groups could also be called 'epistemic communities' as used by Roth (2006) [12] where epistemic communities are understood as a descriptive instance only, not as a coalition of people who have some interest to stay in the community: it is a set of agents who participate in building the same knowledge.

Camille Roth, "Co-evolution in Epistemic Networks Reconstructing Social Complex Systems", Structure and Dynamics: eJournal of Anthropological and Related Sciences : Vol. 1: No. 3, Article 2, 2006.