A hybrid sentiment analysis method for Turkish

Authors

BUKET ERŞAHİN
ÖZLEM AKTAŞ
DENİZ KILINÇ
MUSTAFA ERŞAHİN

DOI

10.3906/elk-1808-189

Abstract

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.

Keywords

Sentiment analysis, opinion mining, social media, natural language processing

First Page

1780

Last Page

1793

Recommended Citation

ERŞAHİN, BUKET; AKTAŞ, ÖZLEM; KILINÇ, DENİZ; and ERŞAHİN, MUSTAFA (2019) "A hybrid sentiment analysis method for Turkish," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 27: No. 3, Article 16. https://doi.org/10.3906/elk-1808-189
Available at: https://journals.tubitak.gov.tr/elektrik/vol27/iss3/16