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International Journal of Information and Communication Technology Research (IJICT، جلد ۱۴، شماره ۴، صفحات ۴۶-۵۴
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Stance Detection Dataset for Persian Tweets |
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| چکیده انگلیسی 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 3813 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 F1-score of 58%. Moreover, our dataset can facilitate research in some fields in Persian such as cross-lingual stance detection, author profiling, etc. |
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| کلیدواژه‌های انگلیسی مقاله |
stance detection, fake news, social media, twitter, Persian dataset, author profiling |
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| نویسندگان مقاله |
| 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
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| نشانی اینترنتی |
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-4430-1&slc_lang=en&sid=1 |
| فایل مقاله |
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| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
فناوری اطلاعات |
| نوع مقاله منتشر شده |
کاربردی |
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