Sentiment Analysis of Twitter: Turkey Earthquake 2023 Case
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
CEUR-WS
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The most devastating earthquake in the past 20 years was February 6, 2023. The earthquake occurred in southern Turkey near the northern Syrian border. Thousands of people died and many more were left homeless, due to the magnitude of the event, it quickly spread all over the world. The earthquake and its damage were discussed and analyzed from all sides. In this paper, a separate analysis was proposed for tweets posted within 14 days after the earthquake. In this analysis to classify tweets, one type of label did not depend as in previous works that have been done on text classification, but three different types of labels (Manual label, NLTK_VADER label, and Cluster label) are created to classify text tweets by using machine learning algorithms. Then by using the Jaccard similarity coefficient and the cosine similarity measure the two AI labels (NLTK_VADER and Cluster) are compared which result is closer to manual labeling, according to the number of categories (positive, negative, and natural) and accuracy of sentiment in each label. In the result, we have reached that the accuracy of the VADER labeling is more effective than Cluster labeling because its accuracy is much closer to the Manual labeling. © 2024 Copyright for this paper by its authors.
Açıklama
1st International Conference on Smart Automation and Robotics for Future Industry, SMARTINDUSTRY 2024 -- 18 April 2024 through 20 April 2024 -- Lviv -- 200057
Anahtar Kelimeler
Cluster, Machine learning, NLTK VADER, Text classification, Turkey Earthquake
Kaynak
CEUR Workshop Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
3699
