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Published since 1998
ISSN 1562-5419
16+
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Solving the Problem of Classifying the Emotional Tone of a Message with Determining the Most Appropriate Neural Network Architecture

Danis Ilmasovich Bagautdinov, Salman Salman, Vladislav Alekseevich Alekseev, Rustamdzhon Murodzhonovich Usmonov
396-413
Abstract:

To determine the most effective approach for solving the task of classifying the emotional tone of a message, we trained selected neural network models on various sets of training data. Next, based on the performance metric of the percentage of correctly classified responses on a test data set, we compared combinations of training data sets and various models trained on them. During the writing of this article, we trained four neural network models on three different sets of training data. By comparing the accuracy of the responses from each model trained on different training data sets, conclusions were drawn regarding the neural network model best suited for solving the task at hand.

Keywords: NLP, sentiment detection, neural networks, comparison of neural network models, LSTM, CNN, BiLSTM.
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Russian Digital Libraries Journal

ISSN 1562-5419

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