The main objective of the article is to describe the basics of using data on the activity/passivity of social network users and gadget owners, as well as related challenges. Using the method of content analysis, we consider the profile in the social network as the profile of the identity of the owner. Through the prism of presence/absence of information, we can assume who is this or that user. Based on various criteria, we can determine to which category a particular user can be attributed. We consider the profile in the network as a place of confession for the user, and the gadget considered as “prosthesis” that everyone needs to achieve their goals. Therefore, the person and the gadget are considered holistic. We provide information on the development of the OCEAN method, which allows us to «measure» the human psyche based on auto-expression on a social network. We present examples of using users data by Cambridge Analytics for political purposes, such as the 2016 presidential election in the USA, Brexit, and examples showing global data collection, high data representativeness, automating data collection processes, processing information from social network users and their profiling. To demonstrate the level of representativeness of the data, we compared the number of Facebook users in the USA with a population of this country. For comparison purpose, we also analyzed the statistics of users of the Android system. Based on the methods of induction and deduction, as a result, we presented the problems associated with the use of information of gadgets owners (identity theft, using data for manipulation (political and consumer) purpose, threats to democratic elections and the loss of subjectivity in the decision-making process). We also noted the trend (disappointment of people who understand the situation in the political system as a whole), which will develop as a reaction to these processes. As a conclusion, we propose solutions that can reduce negative processes (improving legislation at the international and national level, promoting awareness). The significance of this study for science and society is to clarify the problems associated with big data, which often remain outside the scope of discussion.
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