Bidirectional Encoder Representations from Transformers (BERT) has gained increasing
attention from researchers and practitioners as it has proven to be an invaluable technique …

Abstract Foundation and Large Language Models (FLLMs) are models that are trained using
a massive amount of data with the intent to perform a variety of downstream tasks. FLLMs …

This paper provides an overview of the WANLP 2021 shared task on sarcasm and sentiment
detection in Arabic. The shared task has two subtasks: sarcasm detection (subtask 1) and …

Social media networking is a prominent topic in real life, particularly at the current moment.
The impact of comments has been investigated in several studies. Twitter, Facebook, and …

On social media platforms, it is essential to express one's thoughts, opinions, and reviews.
One of the most widely used linguistic forms to criticize or express a person's ideas with …

Automatic sarcasm detection from text is one important research task in text mining and
natural language processing and has attracted extensive attention from researchers. Most …

In the modern era, posting sarcastic comments on social media became the common trend.
Sarcasm is often used by people to taunt or pester others. It is frequently expressed through …

Sarcasm detection in dialogues has been gaining popularity among natural language
processing (NLP) researchers with the increased use of conversational threads on social …

The rapid progress in deep learning has propelled transformer-based models to the
forefront, establishing them as leading solutions for a multiple NLP tasks. These tasks span …

Customer satisfaction and loyalty are essential for every business. Feedback prediction and
social media classification are crucial and play a key role in accurately identifying customer …