Work

A Deep Learning Approach to Sentiment Analysis in Turkish

Year: 2018

Type: conference-paper

Abstract: This study proposes using deep learning for sentiment analysis in Turkish. Traditional machine learning methods such as logistic regression or Naive Bayes are often applied to this problem however their applicability is limited since they use bag-of-words model which does not take into account the order of the words in a sentence. In this study we compare these approaches with a modern technique called recurrent neural networks using LSTM units on a dataset crawled from Turkish shopping and movie websites. Our results show that RNN based approaches improve the classification accuracies.

Source: International Artificial Intelligence and Data Processing Symposium (IDAP)

DOI: 10.1109/idap.2018.8620751

Authors: Basri Ciftci, Mehmet Serkan Apaydin

Institution: Istanbul Şehir University

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2913458235

FWCI: 1.525

Cites: 10

Cited by: 37

Related to: 10