Novel Turkish Sentiment Analysis
System using ConvNet
Saed Alqaraleh
Computer
Engineering Department, Hasan Kalyoncu University, Turkey
Abstract: In this paper, an efficient model for the
Turkish language sentiment analysis has been introduced. As Turkish is
an agglutinative language, which requires spatial processing, an efficient
pre-processing model was also implemented and integrated as a part of the
developed system. In addition, the Deep Convolutional Neural Networks (ConvNet)
have been integrated to build an efficient system.
Several experiments using the “Turkish
movie reviews” dataset have been conducted, and it has been observed that the developed
system has improved the sentiment analysis system that supports the Turkish
language and significantly outperforms the existing state-of-the-art Turkish
sentiment analysis systems.
Keywords: Sentiment analysis, opinion mining, text
classification, turkish language, convolutional neural networks, natural
language processing.
Received January 8, 2020;
accepted February 21, 2021