Stance Detection Dataset for Persian Tweets

سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 170

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شناسه ملی سند علمی:

JR_ITRC-14-4_006

تاریخ نمایه سازی: 8 بهمن 1401

چکیده مقاله:

Stance detection aims to identify an author's stance towards a specific topic which has become a critical component in applications such as fake news detection, claim validation, author profiling, etc. However, while the stance is easily detected by humans, machine learning models are falling short of this task. In the English language, due to having large and appropriate e datasets, relatively good accuracy has been achieved in this field, but in the Persian language, due to the lack of data, we have not made significant progress in stance detection. So, in this paper, we present a stance detection dataset that contains ۳۸۱۳ labeled tweets. We provide a detailed description of the newly created dataset and develop deep learning models on it. Our best model achieves a macro-average F۱-score of ۵۸%. Moreover, our dataset can facilitate research in some fields in Persian such as cross-lingual stance detection, author profiling, etc.

نویسندگان

Mohammad Hadi Bokaei

ICT Research Institute (ITRC) Tehran, Iran

Mojgan Farhoodi

ICT Research Institute (ITRC) Tehran, Iran

Mona Davoudi

ICT Research Institute (ITRC) Tehran, Iran