New Language Identification and Sentiment Analysis Modules for Social Media Communication

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Authors

SABOL Radoslav HORÁK Aleš

Year of publication 2022
Type Article in Proceedings
Conference International Conference on Text, Speech, and Dialogue
MU Faculty or unit

Faculty of Informatics

Citation
Web https://link.springer.com/chapter/10.1007/978-3-031-16270-1_8
Doi http://dx.doi.org/10.1007/978-3-031-16270-1_8
Keywords social media communication; language identification; sentiment analysis
Description In the presented paper, we describe the development and evaluation of new modules specifically designed for language identification and sentiment analysis of informal business communication inside a large international company. Besides the details of the module architectures, we offer a detailed comparison with other state-of-the-art tools for the same purpose and achieve an improvement of 10–13 % in accuracy with selected problematic datasets.
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