  In this paper, we investigate how dynamic properties of reputation can
influence the quality of users ranking. Reputation systems should be based on
rules that can guarantee a high level of trust and help identifying unreliable
units. To understand the effectiveness of dynamic properties in the evaluation
of reputation, we propose our own model (DIB-RM) that is based on three
factors: forgetting, cumulative, and activity period. In order to evaluate the
model, we use data from StackOverflow, which also has its own reputation model.
We estimate similarity of ratings between DIB-RM and the StackOverflow model so
to check our hypothesis. We use two values to calculate our metric: DIB-RM
reputation and $historical$ reputation. We found that $historical$ reputation
gives better metric values. Our preliminary results are presented for different
sets of values of the aforementioned factors in order to analyze how
effectively the model can be used for modeling reputation systems.
