PS Playground
Here you can download the spreadsheet with existing simulation and guidance to build new ones.
Steps to repeat the simulation, or generate new ones
Set the number of periods you want to run the model for (in our case, 10) and specify the TCM values for each period. In our scenario, TCM grows 10x (1000%) for the first 5 periods, then decreases 20x (2000%) from the 6th period to the 10th.
Specify values for each period. This can be any value between 1 and 10, doesn’t need to be an integer (in real scenarios, it’s quite unlikely to be an integer).
Assign individual commitment levels (iCL) to each member for each period.
In this simulation:
Member 1: iCL oscillates between 5 and 6 (10% fluctuation)
Member 2: iCL oscillates between 3 and 4 (10% fluctuation)
Member 3: iCL goes from 10 to 1 (90% fluctuation)
Calculate the fractional CL (fiCL) using the formula , this will save you a lot of time and computation.
Determine the total contribution points (TCP) for each period.
Make sure to use the constraint , this way you’ll be able to simulate more realistic community’s dynamics.
Use the general formula for the expected contributions (ECp) → .
We used a constant value of → (105%), but you could use different values for each period or member. This way you can add additional stress to the system.
You may use the reverse formula to find Given Contributions’ value as
We started with an initial Participation Score for each member. You may start with any value you please. Calculate the subsequent scores using the general formula . Please make sure you include the exceptions, constraints and checks included in the general docs (here).
Analyze the results and draw your own conclusions. If anything weird comes up, please contact us - if it’s a new edge-case we didn’t consider, we may even have a bounty for you :)
By following these steps and adjusting the parameters and stress test conditions, you can create new simulations to explore different scenarios - or to gain insights into the participation and reputation dynamics within an existing community.
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