Comparative Approaches to Sentiment Analysis using Datasets in Major European and Arabic Languages
Year: 2025
Type: conference-paper
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’s 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.
Institution: Instituto Politécnico Nacional
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Awards: G3488607286, G6958583472
OpenAlex ID: W4406774496