Stance Detection Dataset for Persian Tweets
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 s...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Iran Telecom Research Center
2022-12-01
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| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-544-en.html |
| _version_ | 1828039246690123776 |
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| author | Mohammad Hadi Bokaei Mojgan Farhoodi Mona Davoudi |
| author_facet | Mohammad Hadi Bokaei Mojgan Farhoodi Mona Davoudi |
| author_sort | Mohammad Hadi Bokaei |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T16:38:59Z |
| format | Article |
| id | doaj.art-79a83ae543af4779b854edb83e18c187 |
| institution | Directory Open Access Journal |
| issn | 2251-6107 2783-4425 |
| language | English |
| last_indexed | 2024-04-10T16:38:59Z |
| publishDate | 2022-12-01 |
| publisher | Iran Telecom Research Center |
| record_format | Article |
| series | International Journal of Information and Communication Technology Research |
| spelling | doaj.art-79a83ae543af4779b854edb83e18c1872023-02-08T08:02:51ZengIran Telecom Research CenterInternational Journal of Information and Communication Technology Research2251-61072783-44252022-12-011444654Stance Detection Dataset for Persian TweetsMohammad Hadi Bokaei0Mojgan Farhoodi1Mona Davoudi2 ICT Research Institute (ITRC) Tehran, Iran ICT Research Institute (ITRC) Tehran, Iran ICT Research Institute (ITRC) Tehran, Iran 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.http://ijict.itrc.ac.ir/article-1-544-en.htmlstance detectionfake newssocial mediatwitterpersian datasetauthor profiling |
| spellingShingle | Mohammad Hadi Bokaei Mojgan Farhoodi Mona Davoudi Stance Detection Dataset for Persian Tweets International Journal of Information and Communication Technology Research stance detection fake news social media persian dataset author profiling |
| title | Stance Detection Dataset for Persian Tweets |
| title_full | Stance Detection Dataset for Persian Tweets |
| title_fullStr | Stance Detection Dataset for Persian Tweets |
| title_full_unstemmed | Stance Detection Dataset for Persian Tweets |
| title_short | Stance Detection Dataset for Persian Tweets |
| title_sort | stance detection dataset for persian tweets |
| topic | stance detection fake news social media persian dataset author profiling |
| url | http://ijict.itrc.ac.ir/article-1-544-en.html |
| work_keys_str_mv | AT mohammadhadibokaei stancedetectiondatasetforpersiantweets AT mojganfarhoodi stancedetectiondatasetforpersiantweets AT monadavoudi stancedetectiondatasetforpersiantweets |