Virtual Communication and Social Networks Virtual Communication and Social Networks Виртуальная коммуникация и социальные сети 2782-4799 2782-4802 56007 10.21603/2782-4799-2022-1-4-215-220 ПСИХОЛОГИЯ И СОЦИОЛОГИЯ ВИРТУАЛЬНОЙ КОММУНИКАЦИИ И СОЦИАЛЬНЫХ СЕТЕЙ PSYCHOLOGY AND SOCIOLOGY OF VIRTUAL COMMUNICATION AND SOCIAL NETWORKS ПСИХОЛОГИЯ И СОЦИОЛОГИЯ ВИРТУАЛЬНОЙ КОММУНИКАЦИИ И СОЦИАЛЬНЫХ СЕТЕЙ Cross-Regional Sentiment Analysis of VKontakte Communities: Typical Krasnodar vs. Typical Kemerovo Кросс-региональный анализ настроений пользователей сетевых сообществ ВКонтакте «Типичный Краснодар» и «Типичный Кемерово» Рябченко Наталья Анатольевна Ryabchenko Natal'ya Anatol'evna Малышева Ольга Петровна Malysheva Ol'ga Petrovna Кубанский государственный университет Краснодар Россия Kuban State University Krasnodar Russian Federation Кубанский государственный университет Краснодар Россия Kuban State University Krasnodar Russian Federation 22 12 2022 22 12 2022 1 4 215 220 02 09 2022 02 12 2022 https://vestnik-hss.kemsu.ru/en/nauka/article/56007/view

Исследование посвящено описанию комплексного метода анализа сетевых лингвистических данных, основанного на семантическом моделировании дискурсивных полей и сетевом анализе. Анализ глобальных дискурсивных полей как социальных графов посредством визуализации и анализа семантических ядер позволяет оперативно выявлять тематики, вызывающие широкий общественный резонанс, и проводить предиктивную аналитику вектора культурных и социально-политических тенденций. Результаты позволили предложить органам власти ряд рекомендаций по организации эффективного информационного управления и нивелирования социальной напряженности в регионах за счет дискурсивного регулирования коммуникативных процессов в онлайн-пространстве.

This research tested a complex analytical method based on semantic modeling of discursive fields and network analysis that can be applied to networked linguistic data. The copyright software package Monitoring and Analysis of Social Networks, Internet Communities, and Users provided automatic data processing to restore the semantic core of the discursive fields generated by Typical Krasnodar and Typical Kemerovo online communities in 2021–2022. The analysis was visualized as social graphs and semantic core models. It identified a number of sensitive topics that generated a lot of feedback. The method also proved efficient in predicting cultural and socio-political trends. The complex methodology provided rapid identification of amplified discursive activity, conditions for social unrest, and bifurcation points for destructive social practices. The results may contribute to effective information management and social strain relief in the regions through discursive control of online communication.

 дискурсивные поля онлайн-сообщества семантическое ядро сетевая лингвистика социальные медиа ВКонтакте сетевые лингвистические данные discursive fields online communities semantic core network linguistics social media VKontakte network linguistic data Исследование выполнено при финансовой поддержке РФФИ (Отделение гуманитарных и общественных наук) в рамках научного проекта № 20-012-00033 «Лингвистические модели социально-­политической коммуникации в online-пространстве: дискурсивные поля, паттерны и гибридная методология анализа сетевых данных» (2020–2022 гг., рук. В. В. Катермина). The research was supported by The Russian Foundation for Basic Research (Department of Humanitarian and Social Science), research project no. 20-012-00033: Linguistic models of sociopolitical online communication: discursive fields, patterns, and hybrid methodology of network data analysis (2020–2022; project leader – V. V. Katermina).

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