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.

The Potential of Cognitive Social Mining Applications in Data Analytics for Protecting Social Media Users for National and International Security

Using social media has become an integral part of life for people of different demographics for information exchange, searching, maintaining contact networks, marketing, locating job opportunities etc. Social networking is used for education, research, business, advertisements and entertainment. Social media platforms are prone to cybercrime, which is a threat not only for the individual user but for national and international security according to the National Security Council Report. With the advent of big data storage and analytics abilities, decision making is a potential problem and requires smarter machines to organize data faster, make better sense of it, discover insights, learn, adapt and improve over time without direct programming. Cognitive computing makes it easy to unveil the patterns hidden in unstructured data and make more informed decision on consequential matters. In this chapter is a discussion of the challenges and opportunities in social mining services and the applications of cognitive technology towards national security.