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Sentiment Classification on Thai Social Media Using a Domain-Specific Trained Lexicon

Social media contains many valuable documents which can be used to retrieve insights into any targeted topic. Sentiment analysis is a task to extract opinions of people out of their writing. Although a method using a sentiment lexicon is suitable for sentiment classification on social media documents, a lexicon created without consideration of any specific topic domain may not reflect actual intention in the domain of the considered documents. This study compares a sentiment lexicon created from documents in a specific domain with a generic lexicon. The experimental results show that using a specific lexicon improves classification performance, particularly on documents having non-neutral sentiment.