  A simple dynamical model of collective edit activity of Wikipedia articles
and their content evolution is introduced. Based on the recent empirical
findings, each editor in the model is characterized by an ability to make
content edit, i.e., improving the article by adding content and a tendency to
make maintenance edit, i.e., dealing with formal aspects and maintaining the
edit flow. In addition, each article is characterized by a level of maturity as
compared to a potential quality needed to comprehensively cover its topic. This
model is found to reproduce the basic structure of the bipartite network
between editors and articles of Wikipedia. Furthermore, the relation between
the model parameters of editors and articles and the metrics of those
calculated from the emergent network turns out to be robust, i.e. depending
only on the rate of the introduction of new articles to the editing activity.
This results provides us a way to relate observations in the real data to the
hidden characteristics of editors and articles. For the nestedness of the
networks, systems with weighted parameter distribution gives better match to
the empirical one. This suggests the importance of high-dimensional nature of
the ability of editors and quality of articles in the real system.
