Exploring multilingual reviews for aspect-based sentiment analysis using Lexicon and BERT

Abstract

Microblogs and social media sites have gained a central place and people use these platforms to express their opinions, sentiments, and thoughts about products, news, events, blogs, etc. Sentiment analysis is the process of exploring opinions and sentiments in user reviews and tweets. This area is still in its early developmental phase and requires imperative improve-ments on various issues. One of the main issues is multilingual tweets and reviews. Earlier sen-timent analysis techniques only classified the text of a specific language, i.e., English, Turkish, etc. The accuracy of these techniques decreases in the presence of multilingual text. Existing methods are domain oriented. Using BERT and a lexicon, we propose a method for sorting out multilingual text and improving the polarity calculation of reviews. Experimental results reveal that our proposed technique achieved 90.14% accuracy and outperformed existing as-pect-based sentiment analysis techniques.

Keywords

• BERT
• Lexicon
• SentiWordNet
• Sentiments
• Social Media

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