Humor Detection in Persian: A Transformers-Based Approach
Publish place: International Journal of Information and Communication Technology Research (IJICT، Vol: 15، Issue: 1
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_ITRC-15-1_006
تاریخ نمایه سازی: 10 اردیبهشت 1402
Abstract:
Humor is a linguistic device that can make people laugh, and in the case of expressing opinions, it can transform a phrase's polarity. Humorous sentences presenting ideas and criticism, occasionally using informal forms, have made their way to social media platforms like Twitter in almost every domain. Persian speakers likewise express their opinions through humorous tweets on Twitter. As one of the early efforts for detecting humor in Persian, the current research proposes a model by fine-tuning a transformer-based language model on a Persian humor detection dataset. The proposed model has an accuracy of ۸۴.۷% on the test set. Moreover, This research introduced a dataset of ۱۴,۹۴۶ automatically-labeled tweets for humor detection in Persian.
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Authors
Fateme Najafi-Lapavandani
Faculty of Mathematics & Computer Science Amirkabir University of Technology Tehran, Iran
Mohammad Hasan Shirali-Shahreza
Faculty of Mathematics & Computer Science Amirkabir University of Technology Tehran, Iran