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The paper discusses the development of a corpus of Russian ministerial posts based on VKontakte social network. The study is aimed at revealing topical structure of ministerial communities. We performed a series of experiments which include LDA topic modeling and automatic topic labeling that help to improve the interpretability of topics. To implement the procedures, we used Python libraries for NLP. Experiments allowed us to find out pivotal topics that the government of Russia covers on social networks nowadays.
Язык оригиналаанглийский
Название основной публикацииProceedings of the Computational Models in Language and Speech Workshop (CMLS 2020) co-located with 16th International Conference on Computational and Cognitive Linguistics (TEL 2020)
РедакторыAlexander Elizarov, Natalia Loukachevitch
Страницы32-42
СостояниеОпубликовано - 18 дек 2020
СобытиеComputational Models in Language and Speech & 16th International Conference on Computational and Cognitive Linguistics - Kazan, Российская Федерация
Продолжительность: 12 ноя 202013 ноя 2020

Серия публикаций

НазваниеCEUR workshop proceedings
Том2780
ISSN (печатное издание)1613-0073

конференция

конференцияComputational Models in Language and Speech & 16th International Conference on Computational and Cognitive Linguistics
Сокращенное названиеCMLS 2020 - TEL 2020
Страна/TерриторияРоссийская Федерация
ГородKazan
Период12/11/2013/11/20

ID: 71955294