TY  - JOUR
TI  - SENTIMENT CLASSIFICATION ON TURKISH TWEETS ABOUT COVID-19 USING  LSTM NETWORK
AB  - 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.
AU  - Çataltaş, Mustafa
AU  - Üstünel, Büşra
AU  - Baykan, Nurdan
DO  - 10.36306/konjes.1173939
PY  - 2023
JO  - Konya mühendislik bilimleri dergisi (Online)
VL  - 11
IS  - 2
SN  - 2667-8055
SP  - 341
EP  - 353
DB  - TRDizin
UR  - http://search/yayin/detay/1180910
ER  -