In this paper, we consider the problem of determining politico-ideological preferences of users of online social networks. We propose a (DLS) model that allows assessing politico-ideological preferences of VKontakte users using information from their accounts (digital footprints). The model meets the main ideological directions in modern-day Russia. Our approach is based on the supervised learning methodology whereby one solves a classification problem by calculating posterior probabilities of class membership. We compile an anonymized labeled dataset and develop appropriate software. Then we formulate and solve the problem of the politician’s choice of an ideological positioning strategy that will potentially receive the most support from the considered set of users. We exemplify our methodology by finding “ideal” political positioning for some popular online communities in VKontakte.