SENTIMENT CLASSIFICATION ON TURKISH TWEETS ABOUT COVID-19 USING LSTM NETWORK

Authors : Mustafa ÇATALTAŞ, Büşra ÜSTÜNEL, Nurdan AKHAN BAYKAN

Pages : 341-353

Doi:10.36306/konjes.1173939

View : 119 | Download : 91

Publication Date : 2023-06-01

Article Type : Research Paper

Abstract :As Covid-19 pandemic affected everyone in various aspects, people have been expressing their opinions on these aspects mostly on social media platforms because of the pandemic. These opinions play a crucial role in understanding the sentiments towards the pandemic. In this study, Turkish tweets on Covid-19 topic were collected from March 2020 to January 2021 and labelled as positive, negative, or neutral in terms of sentiment using BERT which is a pre-trained text classifier model. Using this labelled dataset, a set of experiments were carried out with SVM, Naive Bayes, K-Nearest Neighbors, and CNN-LSTM model machine learning algorithms for binary and multi-class classification tasks. Results of these experiments have shown that CNN-LSTM model outperforms other machine learning algorithms which are used in this study in both binary classification and multi-class classification tasks.
Keywords : Duygu Analizi, Türkçe Twitter, Sınıflandırma, LSTM