2022

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Sarcasm detection in urdu using tweets data
(UMT, Lahore, 2022) Shanzay Gul
An essential task in sentiment analysis is the automatic detection of sarcasm in textual data. Because sarcastic remarks can convey the opposite meaning and depend on context, this situation is complicated. Due to the dearth of linguistic resources online, identifying sarcasm in comments written in Urdu text poses an even more challenging problem. In this research, we have performed sarcasm detection in Urdu using tweet data. We have used the iSarcasm Eval dataset which is a labeled dataset. We translated English tweets into Urdu tweets using Google Translator and then trained the model to perform sentimental analysis on it using Supervised learning to detect sarcasm. We used SVM and logistic regression using BOW and TF-Idf. We got the accuracy of the results 70%,67%, and 74% for logistic regression using BOW, logistic regression using TF-Idf, and SVM using BOW respectively.