Population Dynamics and evolutionary game theory are the next two step in this paradigm.
However to perform meaningful population dynamics it is necessary to
- catalogue relevant social roles.
- identify methods for tracking users within these roles.
- check that these roles cover the population of the community fairly well.
- extract populations sizes and incidents from database and or dumps.
- generate time series from the above.
- explore how populations in roles participation in correlated rise and fall of population/incidents
- build models using differential equations relating interrelated games.
- ask the research questions which model M(G_I,...G_N) fit patterns in #6
- ask the research question can models from #8 be used predictively.
Evolutionary game theoretic models
With a working system of differential equations we can ask a bunch of new research question and simulate for the answer.
- how will changing some parameter cause the system to evolve effect populations/player strategy/game rules/pay-offs/costs.
- how will choices between one of serveral policies effect the above (this is a special case of changing game rules).
- how will changing software effect the above (this is a special case of changing technology).
Using an evolutionary models we might predict creation/extinction of states/roles/events in the system as well as possible time-frames. an Example application would be to try to measure the impact of upcoming technologies such as wikidata, visual editor, flow (new talk pages) and echo (notification).
However it still remains to be seen if this approach can be useful - after all even if the simulation predicts a new role arising - can we understand what it will actualy mean in the new context.
Since the above two programs are too ambitions even for a single crackpot researcher, I have developed some of these ideas into a new paradigm which is a light wieght frame work to use Wiki game theory to solve practical community problems and surprisingly it uses Gamification and SNA as well.