Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languages

• URL: http://arxiv.org/abs/2501.12540v1
• Date: Tue, 21 Jan 2025 23:11:16 GMT
• Title: Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languages
• Authors: Mikhail Krasitskii, Olga Kolesnikova, Liliana Chanona Hernandez, Grigori Sidorov, Alexander Gelbukh,
• Abstract summary: This study explores transformer-based models such as BERT, mBERT, and XLM-R for multi-lingual sentiment analysis.<n>Key contributions include the identification of XLM-R superior adaptability in morphologically complex languages, achieving accuracy levels above 88%.
• Score: 42.90274643419224
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This study explores transformer-based models such as BERT, mBERT, and XLM-R for multi-lingual sentiment analysis across diverse linguistic structures. Key contributions include the identification of XLM-R superior adaptability in morphologically complex languages, achieving accuracy levels above 88%. The work highlights fine-tuning strategies and emphasizes their significance for improving sentiment classification in underrepresented languages.

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