Abstract
Currently, the problem of efficient gathering and analysis of heterogeneous data from public Internet sources is relevant to many companies working with social issues. Also it applies to the task of building a social profile for the subsequent person identification. This paper addresses the issues of direct and indirect identification a person on the Internet as well as data structure development to store the static and dynamic information of a personal social profile. The article considers the basic options of personal network identification such as an identification by profiling data, IDs, personal websites and blogs, accounts in social networks, e-mail addresses and links from other resources. After identifying it is necessary to collect and structure the detected data about a person. For this purpose, the authors proposed a basic data structure divided into static and dynamic parts. The static part is represented in the form of a relational database and contains immutable data that uniquely identify a specific human (for example, name and surname, completed educational institutions, career, curriculum vitae etc.). The dynamic part is organized as a NoSQL store and accumulates all the information about the current human activity in the network (for examples, accounts in social networks, network friends, current preferences when buying products, preferences when visiting network resources, political and social beliefs etc.).
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Timonin, A.Y., Bozhday, A.S., Bershadsky, A.M. (2016). The Process of Personal Identification and Data Gathering Based on Big Data Technologies for Social Profiles. In: Chugunov, A., Bolgov, R., Kabanov, Y., Kampis, G., Wimmer, M. (eds) Digital Transformation and Global Society. DTGS 2016. Communications in Computer and Information Science, vol 674. Springer, Cham. https://doi.org/10.1007/978-3-319-49700-6_57
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