A transformer-based generative adversarial learning to detect sarcasm from Bengali text with correct classification of confusing text

SK Lora, I Jahan, R Hussain, R Shahriyar… - Heliyon, 2023 - cell.com
Sarcasm detection research in Bengali is still limited due to a lack of relevant resources. In
this context, getting high-quality annotated data is costly and time-consuming. Therefore, in …

Interpretable bangla sarcasm detection using bert and explainable ai

R Anan, TS Apon, ZT Hossain… - 2023 IEEE 13th …, 2023 - ieeexplore.ieee.org
A positive phrase or a sentence with an underlying negative motive is usually defined as
sarcasm that is widely used in today's social media platforms such as Facebook, Twitter …

[PDF][PDF] Sarcasm Identification in Dravidian Languages Tamil and Malayalam.

P Shetty - FIRE (Working Notes), 2023 - ceur-ws.org
Sarcasm poses a formidable challenge to sentiment analysis systems as it conveys opinions
indirectly, often diverging from their literal interpretation. The escalating demand for sarcasm …

Sentiment Analysis in the Transformative Era of Machine Learning: A Comprehensive Review

SM Ferdous, SNE Newaz, SBS Mugdha… - Statistics, Optimization & …, 2025 - iapress.org
Sentiment analysis, which stands for opinion mining, is a natural language processing (NLP)
technique that involves identifying, extracting, and analyzing sentiments or opinions …

Comparative Analysis of Traditional and Contextual Embedding for Bangla Sarcasm Detection in Natural Language Processing

KMH Fahim, M Moontaha, M Rahman… - … Networks and Satellite …, 2023 - ieeexplore.ieee.org
Sarcasm, a sort of sentiment characterized by a disparity between the apparent and
intended meanings of the text, is a key component of sentiment analysis, opinion extraction …

A Machine Learning approach to Data Augmentation with Semantic Similarity on a Low-Resource Language

SJ Islam, MA Chowdhury, T Alam - 2023 - 103.82.172.44
The augmentation of data in low-resource languages gained significant importance re
cently, primarily because of scarcity of datasets or the presence of highly unbalanced …