An automated approach to identify sarcasm in low-resource language

HIGHLIGHTS

• What: By conducting a comparative study of various state-of-the-art ML models, the authors aim to recognize the most effective model for sarcasm detection in Urdu, which can serve as a benchmark for future studies. The study focused on classifying the instances of sarcasm in Urdu, as it significantly enhances NLP research and facilitates practical applications over diverse domains. The study aims to comprehensively understand the methods and techniques employed in sentiment analysis for Urdu. 3 Proposed research approach This study explores tweets from user-generated comments on X, previously Twitter, explicitly concentrating on low . . .
  

   

  

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