Approaches of the development of information monitoring system of social wellness opinions and evaluation
DOI:
https://doi.org/10.26577/JMMCS-2018-4-574Keywords:
social media monitoring, comment analysis, social well-being, a user’s perception evaluationAbstract
A dynamic spreading of social on-line services and development of the Big Data technologies have caused interest to use information from social media in different spheres. Nowadays the "social listening” and content analysis technologies gain popularity. The given services are basically represented by foreign development works, where linguistic dictionaries are made in English and they are badly adapted to Russian and Kazakh.
The given article describes the process of designing and developing the information system to monitor “social media”, adapted to the specific character of the Kazakh and Russian languages and forms of slang communication as well to define the emotional coloring of a user’s perception of the content and evaluation of the social well-being in the region and country. The work represents the algorithm of the information system describing functionalities and methods and models as well. Besides, a production model of social well-being evaluation and a semantic profile model for conceiving events by society has been considered. A comparative analysis of the development works has been made in the issues of opinions monitoring to reveal strengths and weaknesses. The information system gives an opportunity to monitor mass and social media, to analyze reputation management, to analyze a user’s perception of the Internet content on the regional and a nationwide scale.
References
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[3] Laine M.O.J., Frühwirth C., «Monitoring Social Media: Tools, Characteristics and Implications», International Conference of Software Business (2010): 193-198.
[4] Liu Y., «Social Media Monitoring», Social Media in China (2016), accessed on November 14, 2018, https://doi.org/10.1007/978-3-658-11231-8_10
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[6] Tesconi M., Gazzé D., Duca A.L., «SocialTrends: A Web Application for Monitoring and Visualizing Users in Social Media», International Conference on Social Informatics (2012): 535-538.
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[12] Schinas M., Papadopoulos S., Apostolidis L., Kompatsiaris Y., Mitkas P.A., «Open-Source Monitoring, Search and Analytics Over Social Media», International Conference on Internet Science (2017): 361-369
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[16] Souza R.C.S.N.P., de Brito D.E.F., Cardoso R.L., de Oliveira D.M., Meira W., Pappa G.L., «An Evolutionary Methodology for Handling Data Scarcity and Noise in Monitoring Real Events from Social Media Data», Ibero-American Conference on Artificial Intelligence (2014): 295-306
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[33] Rumyantseva D., «ER - metodyi rascheta i znachenie pokazateley» [ER - calculation methods and indicators], accessed November 29, 2018, https://www.cossa.ru/155/101492/
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How to Cite
Mamykova, Z. D., Mutanov, G. M., Sundetova, Z. T., & Torekul, S. M. (2019). Approaches of the development of information monitoring system of social wellness opinions and evaluation. Journal of Mathematics, Mechanics and Computer Science, 100(4), 63–77. https://doi.org/10.26577/JMMCS-2018-4-574
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Computer Science
