Suchergebnisse

В статье рассматривается потенциал динамического подхода анализа данных в изучении поведения пользователей в социальных сетях. В настоящее время в социальных сетях появляется информация, которая позволяет дифференцировать группы пользователей по их активности в рамках технических возможностей той или иной социальной сети. Представлено описание, дан краткий анализ информационного поля в региональных сообществах Томской области, сформирована кластеризация постов - три сферы жизнедеятельности общества: социальная, экономическая и политическая. Методология: применен динамический подход к анализу данных социальных сетей; осуществлен анализ поведения пользователей, структуры узлов и связей социальных сетей, который позволяет выявить скорость роста или уменьшения размера сети, перераспределение связей между группами. После получения списка информативных и уникальных постов произведен семантический анализ текстов с помощью инструмента для текстовой аналитики PolyAnalyst. Результаты: простроены семантические связи между словами и представлены в виде графов. Выделены два «центра», связывающих все наиболее часто встречающие слова - Томск и Томская область. С помощью инструмента для текстовой аналитики PolyAnalyst выделены популярные персоны и организации. «Позитивный контент» зафиксирован в освещении программы «Безопасные и качественные дороги» в регионе в социальной сети для формирования положительного медиаобраза власти в области. Социально активные пользователи привлекают внимание к социальной тематике. Так, среди наиболее популярных постов наибольшее число посвящено социальной сфере, далее следуют политическая и экономическая. Вместе с тем социальные сети являются также и доступным в настоящее время инструментом манипуляции общественным мнением. ; The paper considers the potential of a dynamic data analysis approach in studying user behavior in social networks. Currently, information appears on social networks that allows differentiating user groups by their activity within the technical capabilities of a particular social network. The paper introduces the description, a brief analysis of the information field in the regional communities of the Tomsk region; the clustering of posts into three spheres of the life of society: social, economic and political, is formed. Methodology. A dynamic approach was used to analyze social media data. The analysis of user behavior, the structure of nodes and connections of social networks is carried out, which makes it possible to identify the rate of growth or decrease in the size of the network, the redistribution of connections between groups. After receiving a list of informative and unique posts, a semantic analysis of the texts was performed using the PolyAnalyst text analytics tool. Results. The semantic connections between words were built and presented in the form of graphs. Two «centers» are highlighted that connect all the most frequently encountered words - Tomsk and Tomsk Oblast. Popular people and organizations are highlighted using the PolyAnalyst text analytics tool. The greatest positive content was recorded in the coverage of the Safe and High-Quality Roads program in the region in the social network to form a positive media image of the authorities in the region. Socially active users draw attention to social topics. So, among the most popular posts, the largest number is devoted to the social sphere, followed by the political and economic. At the same time, social networks are also a currently available tool for manipulating public opinion.

In the context of fundamental changes in the economy and the labor market, the introduction of educational programs in the field of data analysis and machine learning at all levels of education with the priority of integrating mathematical, natural science and socio-humanitarian knowledge becomes important. An overview and analysis of foreign experience and main discussion topics in the development of educational modules for data science and machine learning for adolescents and adolescents is presented.

Studying the network of interpersonal and intergroup interactions between individuals / groups of individuals is carried out with the help of mathematical models. This type of study is called cluster-network analysis. In this article, based on years of his own research in this area is represented by adapting the analysis of networking in terms of social philosophy. Inconclusive nature of the relationship stratification in online communities and describes a method of calculation of social capital.

The report analyzes the relationship between educational and socio-economic indicators using international statistics. Based on the analysis of international databases and a review of literary sources, hypotheses about the relationship between the indicators of educational systems and the effects of education for society, the economy and the individual are formed, methods of analysis are selected, indicators for analysis were chosen.

Рассматриваются основные положения законодательных актов в сфере защиты персональных данных стран Евросоюза, США и СНГ. Проводится анализ основных источников угроз конфиденциальности и целостности баз персональных данных, достоинства и недостатки, как международной законодательной системы, так и законодательной систем Российской Федерации и Украины в области защиты персональных данных, особенности законодательных актов в данной сфере. ; The basic provisions of legislation in the sphere of protection of personal data of EU countries, the USA and the CIS. Analysis of the main sources of threats to the confidentiality and integrity of personal databases, advantages and disadvantages, as the international legal system and the legal system of the Russian Federation and Ukraine in the field of personal data protection features of legislation in this area

The basic provisions of legislation in the sphere of protection of personal data of EU countries, the USA and the CIS. Analysis of the main sources of threats to the confidentiality and integrity of personal databases, advantages and disadvantages, as the international legal system and the legal system of the Russian Federation and Ukraine in the field of personal data protection features of legislation in this area. ; Рассматриваются основные положения законодательных актов в сфере защиты персональных данных стран Евросоюза, США и СНГ. Проводится анализ основных источников угроз конфиденциальности и целостности баз персональных данных, достоинства и недостатки, как международной законодательной системы, так и законодательной систем Российской Федерации и Украины в области защиты персональных данных, особенности законодательных актов в данной сфере. ; Розглядаються основні положення законодавчих актів у сфері захисту персональних даних країн Євросоюзу, США та СНД. Проводиться аналіз основних джерел загроз конфіденційності та цілісності баз персональних даних, переваги і недоліки, як міжнародної законодавчої системи

The purpose of the research: development of mechanisms for optimizing the quality management system of education at various levels in the digital environment based on methods of working with big data.

Рассматриваются основные законодательные акты о защите персональных данных стран Евросоюза, США и стран постсоветского пространства. Проводится анализ основных требований, выдвигаемых к программным и аппаратно-программным средствам защиты персональных данных. ; Розглядаються основні законодавчі акти про захист персональних даних країн Євросоюзу, США і країн пострадянського простору. Проводиться аналіз основних вимог, висунутих до програмних і апаратно-програмних засобів захисту персональних даних. ; Main legislative acts about personal data protection in European Union, USA and post-soviet countries are considered. Analysis of the main requirements to software and hardware- software of personal data protection is made.

Quite often in many areas of human activity, there are tasks of studying the situation, having a large number of various qualities, any of which has the ability to be important for the properties of this system. Information about this system, as a rule, can be presented in the form of an array of descriptions of the qualities of selected research units, referred to as the term "object" autonomously from their nature. The qualities of objects are operationalized with the support of measurement procedures when an object is put in relation to some sense, degree, the gradation of the symptom that carries this property. Thus, we obtain data–marked results of the measurement of symptoms expressing the quality of the array of objects under consideration. When using formal methods of data restructuring, virtually no other information about objects and their properties is taken into account. But, of course, a meaningful test of the results of measurements is quite important, because not every time in advance it is clear what qualities, or their expressing symptoms can be integrated into the study.

The predicted negative trends in Russian demography (falling birth rates, population decline) actualize the need to strengthen measures of family and population policy. Our research purpose is to identify groups of Russian regions with similar characteristics in the family sphere using cluster analysis. The findings should make an important contribution to the field of family policy. We used hierarchical cluster analysis based on the Ward method and the Euclidean distance for segmentation of Russian regions. Clustering is based on four variables, which allowed assessing the family institution in the region. The authors used the data of Federal State Statistics Service from 2010 to 2015. Clustering and profiling of each segment has allowed forming a model of Russian regions depending on the features of the family institution in these regions. The authors revealed four clusters grouping regions with similar problems in the family sphere. This segmentation makes it possible to develop the most relevant family policy measures in each group of regions. Thus, the analysis has shown a high degree of differentiation of the family institution in the regions. This suggests that a unified approach to population problems' solving is far from being effective. To achieve greater results in the implementation of family policy, a differentiated approach is needed. Methods of multidimensional data classification can be successfully applied as a relevant analytical toolkit. Further research could develop the adaptation of multidimensional classification methods to the analysis of the population problems in Russian regions. In particular, the algorithms of nonparametric cluster analysis may be of relevance in future studies. ; Government Council on Grants, Russian Federation ; The article has been supported by the Decree of the Government of the Russian Federation № 211, contract № 02.A03.21.0006.