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Targeted Aspect-Based Sentiment Analysis for Lithuanian Social Media Reviews
Mažvydas Petkevičius, Daiva Vitkutė-Adžgauskienė, Darius Amilevičius
32 - 38
10.3233/FAIA200599
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 328: Human Language Technologies – The Baltic Perspective
Abstract

The paper presents research results for solving the task of targeted aspect-based sentiment analysis in the specific domain of Lithuanian social media reviews. Methodology, system architecture, relevant NLP tools and resources are described, finalized by experimental results showing that our solution is suitable for solving targeted aspect-based sentiment analysis tasks for under-resourced, morphologically rich and flexible word order languages.

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