About a concept of creating a social network users information aggregation and data processing system
https://doi.org/10.21122/2309-4923-2018-4-65-72
Abstract
The development of a general concept and implementation of a data-storage and analysis system for practice oriented data, one of the subsystems of which is an analytical system for the accumulation and analysis of data from users of social networks, is topical. The development of a general concept and implementation of a data-storage and analysis system for practice oriented data, one of the subsystems of which is an analytical system for the accumulation and analysis of data from users of social networks, is topical. Data that users leave about themselves in social networks can be useful in solving various tasks. The proposed article describes the subject area associated with the collection and storage of data from users of social networks. Proceeding from the subject area, the general architecture of the universal data collection and storage system is proposed, which is based on the client-server architecture. For the server side of the system, a fragment of the data model is provided, which is associated with the accumulation of data from external sources. The framework of the system architecture is described. The developed universal system is based on the information technology of data warehousing, and it has the following aspects: an expandable complex subject area, the integration of stored data that come from various sources, the invariance of stored data in time with mandatory labels, relatively high data stability, the search for necessary trade-off in data redundancy, modularity of individual system units, fl and extensibility of the architecture, high security requirements vulnerable data.
The proposed system organizes the process of collecting data and filling the database from external sources. To do this, the system has a module for collecting and converting information from third-party Internet sources and sending them to the database. The system is intended for various users interested in analyzing data of users of social networks.
About the Authors
L. V. Rudikova
Yanka Kupala State University of Grodno
Russian Federation
Lada Rudikova is the Head of Modern Programming Technologies Department. Ph.D. degree in physical and math.
Russian Federation
Lada Rudikova is the Head of Modern Programming Technologies Department. Ph.D. degree in physical and math.
O. R. Myslivec
Yanka Kupala State University of Grodno
Russian Federation
Oleg Myslivec is a lecturer. Master degree in computer science
Russian Federation
Oleg Myslivec is a lecturer. Master degree in computer science
References
1. Rudikova, L. V. On the general architecture of a universal data storage and processing system of practice-oriented orientation / Rudikova // System Analysis and Applied Informatics. – Mn.: BNTU, 2017. – № 2. – P. 12–19.
2. Rudikova, L. V. On modeling data of subject-areas of practice-oriented orientation for a universal system of data warehousing and data processing / L. V. Rudikova, E. V. Zhavnerko // System Analysis and Applied Informatics. – Mn.: BNTU, 2017. – № 3. – P. 19–26.
3. Belyi, A. Global multi-layer network of human mobility /Alexander Belyi, Iva Bojic, Stanislav Sobolevsky, Izabela Sitko, Bartosz Hawelka, Lada Rudikova, Alexander Kurbatski, Carlo Ratti // International Journal of Geographical Information Science. – 2017. – Vol. 31. – P. 1381–1402.
4. Belyi, A. B. Flickr service data and community structure of countries / A.B. Belyi, L.V. Rudikova, S.L. Sobolevsky, A.N. Kurbatski // International Congress on Computer Sciens: Information Systems and Technologies: materials of International Scientific Congress, Republic of Belarus, Minsk, 24 October. – 27 Nov. 2016. / BSU; rare: S.V. Ablameiko (editorial editors) [and others]. – Minsk, 2016. – P. 851–855.
5. Amini A. The impact of social segregation on human mobility in developing and industrialized regions / Amini A, Kung K, Kang C, Sobolevsky S, and Ratti C // EPJ Data Science. – 2014. – 3(1):6.
6. Pei T. A new insight into land use classification based on aggregated mobile phone data / Pei T., Sobolevsky S., Ratti C., Shaw S. L., Li T., Zhou, C. // International Journal of Geographical Information Science. – 2014. – 28(9), P. 1988–2007.
7. Santi P. Quantifying the benefits of vehicle pooling with shareability networks / Santi P., Resta G., Szell M., Sobolevsky S., Strogatz S.H., Ratti C. // Proceedings of the National Academy of Sciences. – 2014. – 111(37). – Рp. 13290–13294.
8. Kung K. Exploring universal patterns in human home/work commuting from mobile phone data / Kung K., Greco K., Sobolevsky S., Ratti C. // PLoS ONE. – 2014. – 9(6):e96180.
9. Hashemian B. Socioeconomic characterization of regions through the lens of individual financial transactions / Hashemian B., Massaro E., Bojic I., Arias J. M., Sobolevsky S., Ratti C. // PloS one – 2017 – 12(11), e0187031.
10. Bojic I. Scaling of foreign attractiveness for countries and states / Bojic I., Belyi, A., Ratt, C., Sobolevsky S. // Applied Geography. – 2016. – 73. – P. 47–52.
11. Sabou M. Visualizing Statistical Linked Knowledge Sources for Decision Support / Sabou M., Hubmann-Haidvogel A., Fischl D., Scharl A. // SemanticWeb. – 2016 – 1. – P. 1–25.
12. Li Q. VisTravel: visualizing tourism network opinion from the user generated content / Li Q., Wu Y., Wang S., Lin M., Feng X., Wang H. // J. Vis. – 2016. – 19. – P. 489–502.
13. Rudikova, L. About laser express expertise system implementation. Monography / Lada Rudikova. – LAP LAMBERT Academic Publishing, 2014. – 134 p.
14. Barseghyan, A. Methods and analysis data models: OLAP and DataMining / A. Barseghyan, M. Kupriyanov, V. Stepanenko, I. Kholod – StP.: BHV-Petersburg, 2009. – 336 p.: il.
15. Paklin, N. Business-analytics: from data to knowledge / N. Paklin, V. Oreshkov. – StP.: Piter, 2009. – 624 p.
16. Информационный центр AfterShock [Электронный ресурс]. – Режим доступа: https://aftershock.news/?q=node/ 479258&full. – Дата доступа: [14.05.2018].
17. Batura, Т. V. Methods of analyzing data from social networks / Т. В. Batura, N. S. Kopylova, F. A. Murzin, A. V. Proskuryakov // Bulletin of NSU. Series: Information technology. – 2013. – Vol. 11, issue. 3. – P. 5–21.
18. ETL environment (extraction, transformation and loading) Rational Insight [Electronic resource]. – Access mode: ht tps://www.ibm.com/support/knowledgecenter/ru/SSRL5J_1.1.1/com.ibm.rational.raer.overview.doc/topics/c_arch_etl_ process.html. – Access date: [14.09.2018].
19. GDPR – new rules for the processing of personal data in Europe for the international IT market [Electronic resource]. – Access mode: https://habr.com/company/digitalrightscenter/blog/344064/. – Access date: [May 14.05.2018].
20. Volushkova V. L. Data structure for storing information in social networks / V. L. Volushkova, A. Y. Volushkova // Educational resources and technologies. – 2014. – 2 (5). – P. 153–157.
Review
For citations:
Rudikova L.V., Myslivec O.R. About a concept of creating a social network users information aggregation and data processing system. «System analysis and applied information science». 2018;(4):65-72. (In Russ.) https://doi.org/10.21122/2309-4923-2018-4-65-72
Views:
1854
Email this article 