Due to the growing trust in information in social media resources, interest in the field of sentiment analysis is growing.
Because sentiment analysis is one of the main technologies for monitoring the opinions of millions of users of social
networks.
The article discusses the use of LSTM networks in the analysis of the tonality of texts in the Kazakh language. For
training the neural network, 1000 user reviews of mobile phones were used. The experiments were carried out in two
ways: in the first case, preprocessing of the analyzed reviews was carried out, in the second case, the preprocessing was
not carried out. The average value of the metric for assessing the quality of the pre-processed model reached 80%. This
indicator is 11% higher than for a model trained on data without preprocessing. The results of the study allowed us to
conclude that the preprocessing of the texts improves the quality of the model.
USING OF LSTM NETWORKS IN SENTIMENT ANALYSIS OF DOCUMENTS IN KAZAKH LANGUAGE
Published June 2021
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Abstract
Language
Қазақ
How to Cite
[1]
Kadyrbek Н., Mansurova М. and Kyrgyzbayeva М. 2021. USING OF LSTM NETWORKS IN SENTIMENT ANALYSIS OF DOCUMENTS IN KAZAKH LANGUAGE. Bulletin of Abai KazNPU. Series of Physical and mathematical sciences. 69, 1 (Jun. 2021), 366–370.