Social network platforms are a useful source of information on preferences of citizens. However, population exposed on social network platform is non representative and in result preferences collected through such platforms are biased. The goal of the public administration is to utilize the data that can be collected through such online platforms in order to understand preferences and its structure in the society and hence better react to community's needs. This situation calls for an algorithm that will allow to generalize information collected on social platform users on the entire population. We propose and evaluate a two-step methodology for testing of such algorithms: (1) synthetic population is generated and its sample is selected that represents social platform users and (2) regenerate the whole population on the basis of data from sub-population. In this way we can evaluate the quality of different algorithms aimed at preference elicitation from social platform data.