Cross-evaluation of social mining for classification of depressed online personas

With the continuous increase in the use of social networks, social mining is steadily becoming a powerful component of digital phenotyping. In this paper we explore social mining for the classification of self-diagnosed depressed users of Reddit as social network. We conduct a cross evaluation study based on two public datasets in order to understand the impact of transfer learning when the data source is virtually the same. We further complement these results with an experiment of transfer learning in post-partum depression classification, using a corpus we have collected for the matter. Our findings show that transfer learning in social mining might still be at an early stage in computational research and we thoroughly discuss its implications.

Social networks and their impact on inter-ethnic relations

The basis of communication, strategies of network interactions is a model of a system of information interactions and an installation on the adaptation of ethnos in a new space. National and cultural ideals of the ethnic group are usually realized in regional policies of inter-ethnic relations, ethnic reflection. Social networks are gradually becoming the main "regulator" of such interactions. The purpose of the work is to systematically analyze these trends, causal relationships and interethnic interactions in social networks. To do this, the work uses the methods of System Social Mining. The analysis allows us to conclude that in Russia “remote nationalism” is possible, associated with the political activities of the diasporas, their activity on social networks.