  Being a matter of cognition, user interests should be apt to classification
independent of the language of users, social network and content of interest
itself. To prove it, we analyze a collection of English and Russian Twitter and
Vkontakte community pages by interests of their followers. First, we create a
model of Major Interests (MaIs) with the help of expert analysis and then
classify a set of pages using machine learning algorithms (SVM, Neural Network,
Naive Bayes, and some other). We take three interest domains that are typical
of both English and Russian-speaking communities: football, rock music,
vegetarianism. The results of classification show a greater correlation between
Russian-Vkontakte and Russian-Twitter pages while English-Twitterpages appear
to provide the highest score.
