There is no deadline - Time evolution of Wikipedia discussions
Kaltenbrunner and Laniado look at the time evolution of Wikipedia discussions, and how it correlates to editing activity, based on 9.4 million comments from the March 12, 2010 dump . Peaks in commenting and peaks in editing often co-occur (for sufficiently large peaks of 20 comments, 63% of the time) within 2 days. They show the articles with the longest comment peaks and most edit peaks, and the 20 slowest and 20 fastest discussions.
They note that a single, heavy editor can be responsible for edit peaks but not comment peaks; peaks in the discussion activity seem to indicate more widespread interest by multiple people. They find that "the fastest growing discussions are more likely to have long lasting edit peaks" and that some editing peaks are associated with event anniversaries. They use the Barack Obama article as a case study, showing peaks in comments and editing due to news events as well as to internal Wikipedia events (such as an editor poll or article protection). Current events are often edited and discussed in nearly real-time in contrast to articles about historical or scientific facts.
They use the h-index to assess the complexity of a discussion, and they chart the growth rate of the discussions. For instance, they find that the discussion pages of the three most recent US Presidents show a constant growth in comments but that the rate of growth varies: Bill Clinton's Talk page took 332 days to increase h-index by one, while George W. Bush's took only 71 days.
"Wikipedia discussions can thus be seen as a mirror of a stream of public consciousness, where those elements which are still not part of a shared consolidated heritage are object of a continuous negotiation among different points of view"
Theoretical and practical relevance:
Could be used for *all articles* in addition to page views and edit count to understand page activity.
They envision more sophisticated algorithms showing the relative growth in edits and discussions. Their ideas for future work are intriguing, for instance to determine article maturity and the level of consensus, based on the network dynamics.