Подходы к разработке информационной системы мониторинга мнений и оценки социального самочувствия
DOI:
https://doi.org/10.26577/JMMCS-2018-4-574Кілттік сөздер:
мониторинг социальных сетей, анализ комментариев, социальное самочувствие, оценка пользовательского восприятияАннотация
Стремительное распространение социальных онлайн-сервисов и развитие технологий Больших Данных инициировали интерес к использованию сведений из социальных сетей в различных отраслях. Сегодня приобретают популярность технологии «мониторинга социальных сетей» (social listening) и контент-анализа. Данные сервисы в основном представлены зарубежными разработками, лингвистические словари, которых построены на английском языке, и они плохо адаптированы под русский и казахский языки.
В представленной статье описан процесс проектирования и разработки информационной системы для «мониторинга социальных сетей», адаптированной под специфику казахского и русского языка, а также форм сленгового общения, с целью определения эмоционального окраса пользовательского восприятия контента, и оценки социального самочувствия в стране/регионе. В работе представлен алгоритм информационной системы с описанием функциональных возможностей, а также методы и модели. Кроме этого, рассматривается продукционная модель оценки социального самочувствия и модель семантического профиля восприятия обществом событий. Проведен сравнительный анализ разработок в вопросах мониторинга мнений для выявления сильных и слабых сторон. Информационная система даст возможность проводить мониторинг СМИ, социальных сетей, анализа управления репутацией, анализа пользовательского восприятия контента сети Интернет на региональном, республиканском и международном уровне.
Библиографиялық сілтемелер
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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.
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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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[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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Как цитировать
Mamykova, Z. D., Mutanov, G. M., Sundetova, Z. T., & Torekul, S. M. (2019). Подходы к разработке информационной системы мониторинга мнений и оценки социального самочувствия. Қазұу Хабаршысы. Математика, механика, информатика сериясы, 100(4), 63–77. https://doi.org/10.26577/JMMCS-2018-4-574
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