Automatic Irony and Sarcasm Detection in Russian Sentences: Baseline Methods
The paper describes experiments performed on two sets of manually annotated data. The task of irony and sarcasm detection in Russian sentences was solved using baseline classifiers, i. e., BERT, Bi-LSTM, SVM, Random Forest, Logistic Regression. The best achieved F1-score for each classifier was 0.76...
Main Authors: | Maksim Kosterin, Ilya Paramonov, Nadezhda Lagutina |
---|---|
Format: | Article |
Language: | English |
Published: |
FRUCT
2023-05-01
|
Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
Subjects: | |
Online Access: | https://www.fruct.org/publications/volume-33/fruct33/files/Kos.pdf |
Similar Items
-
Graph Model for Detection of text unstructured data such as Sarcasm
by: Axel Rodríguez-García, et al.
Published: (2021-01-01) -
Challenges of Sarcasm Detection for Social Network : A Literature Review
by: Afiyati Afiyati, et al.
Published: (2020-11-01) -
A transformer-based generative adversarial learning to detect sarcasm from Bengali text with correct classification of confusing text
by: Sanzana Karim Lora, et al.
Published: (2023-12-01) -
A novel algorithm for sarcasm detection using supervised machine learning approach
by: Abdullah Yahya Abdullah Amer, et al.
Published: (2022-09-01) -
Sarcasm Detection with and without #Sarcasm: Data Science Approach
by: Rupali Amit Bagate, et al.
Published: (2022-10-01)