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

A Comparative Analysis of Social Network Pages by Interests of Their Followers