Abstract
Automatic sentiment analysis is an important technique having a significant impact on many businesses and other fields. Well known fact is that sentiments are culturally dependent phenomena and are differently expressed in various cultural groups. Successful implementation of automatic sentiment identification techniques requires using sentiment corpora. Less widely spoken languages such as Lithuanian often suffer from the lack of corpora, particularly culturally specific corpora. This paper presents the results of an evaluation of the possibilities to apply machine learning techniques and the implementation of other language text corpora for sentiment analysis of texts from representatives of Lithuanian youth subcultures. The results show that quite a high accuracy (about 80–85%) could be achieved at least in some contexts.
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Acknowledgement
This project has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-LIP-21-30.
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Rudzionis, V., Ramanuskaite, E., Kairaityte-Uzupe, A. (2024). Sentiment Analysis of Lithuanian Youth Subcultures Zines Using Automatic Machine Translation. In: Lopata, A., Gudonienė, D., Butkienė, R. (eds) Information and Software Technologies. ICIST 2023. Communications in Computer and Information Science, vol 1979. Springer, Cham. https://doi.org/10.1007/978-3-031-48981-5_16
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DOI: https://doi.org/10.1007/978-3-031-48981-5_16
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