Results of featured-based classifiers.

<div><p>Sarcasm detection has emerged due to its applicability in natural language processing (NLP) but lacks substantial exploration in low-resource languages like Urdu, Arabic, Pashto, and Roman-Urdu. While fewer studies identifying sarcasm have focused on low-resource languages, most...

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Bibliographic Details
Main Author:	Shumaila Khan (11682019) (author)
Other Authors:	Iqbal Qasim (9766143) (author), Wahab Khan (3422642) (author), Aurangzeb Khan (813110) (author), Javed Ali Khan (3396134) (author), Ayman Qahmash (9388861) (author), Yazeed Yasin Ghadi (16667109) (author)
Published:	2024
Subjects:	Sociology Cancer Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified support vector machine providing open access nearest neighbor classifier natural language processing lacks substantial exploration former twitter ). diverse machine learning assessment involved validating resource language becomes primary models evaluated div >< p automatic sarcasm detection dt ), k sarcasm detection research sarcasm detection resource languages nb ), research underscores research addresses identifying sarcasm identify sarcasm detecting sarcasm ml models user ’ png "> given statement generated comments future investigations emerged due comprising user challenging due automated approach annotated datasets
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Results of featured-based classifiers.

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