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.
|Name||CEUR workshop proceedings|
|Conference||Computational Models in Language and Speech & 16th International Conference on Computational and Cognitive Linguistics|
|Abbreviated title||CMLS 2020 - TEL 2020|
|Period||12/11/20 → 13/11/20|