Article detail · 2019
A hybrid sentiment analysis method for Turkish
- Year
- 2019
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Turkish Journal of Electrical Engineering and Computer Sciences
- Catalog match (ISSN) Turkish Journal of Electrical Engineering and Computer Sciences
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
English (OpenAlex)
This paper presents a hybrid methodology for Turkish sentiment analysis, which combines the lexicon-based and machine learning (ML)-based approaches. On the lexicon-based side, we use a sentiment dictionary that is extended with a synonyms lexicon. Besides this, we tackle the classification problem with three supervised classifiers, naive Bayes, support vector machines, and J48, on the ML side. Our hybrid methodology combines these two approaches by generating a new lexicon-based value according to our feature generation algorithm and feeds it as one of the features to machine learning classifiers. Despite the linguistic challenges caused by the morphological structure of Turkish, the experimental results show that it improves the accuracy by 7 % on average.
Topics
- Sentiment Analysis and Opinion Mining
Primary topic Sentiment Analysis and Opinion Mining