Abstract
The paper proposes a new algorithm for formation of training datasets for a neural network that provides sentiment analysis of social network posts. This article also describes the use of a neural network to determine the sentiment values of a social network posts using the word2vec and BERT algorithms. Also conducted experiments confirming the effectiveness of the proposed approaches.
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Acknowledgement
This study was supported by the Russian Foundation for Basic Research (Grants No. 18-47-732007, 18-47-730035 and 19-07-00999).
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Moshkin, V., Konstantinov, A., Yarushkina, N. (2020). Application of the BERT Language Model for Sentiment Analysis of Social Network Posts. In: Kuznetsov, S.O., Panov, A.I., Yakovlev, K.S. (eds) Artificial Intelligence. RCAI 2020. Lecture Notes in Computer Science(), vol 12412. Springer, Cham. https://doi.org/10.1007/978-3-030-59535-7_20
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DOI: https://doi.org/10.1007/978-3-030-59535-7_20
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