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.