Sentiment Analysis with Turkish Adjective Dictionary - Mayda, Islam; Korkmaz, Mehmet (IEEE, 2018)
Today, with the widespread use of the Internet, users are sharing more with online platforms such as social networks and websites. They also pass on their feedbacks on their products and services to both product/service providers and other users via these platforms. This process needs to be automated as the amount of these feedbacks reaches a size that cannot be examined individually by humans. A large number of dictionary-based sentiment analysis studies have been conducted on English texts in the literature. However, the number of studies done in this area for Turkish is very low. Accordingly, in this research, a sentiment analysis study for Turkish customer comments is presented. Within the scope of the study, an adjective dictionary consisting of 9,822 adjectives was scored by the authors in the range [-2, +2]. By using this dictionary, 3-class (positive, negative and neutral) sentiment analysis study was conducted on 2,100 book reviews collected from an online book sales site. Besides the adjective dictionary, the success rate of the study has been increased by developing Turkish language-specific rules. As a result, 61.19% accuracy and 0.5935 F-measurement value were obtained.
Keywords: sentiment analysis; adjective dictionary; lexicon based; CLASSIFICATION; Computer Science; Engineering