Arabic corpora for credibility analysis
المؤلف | Al Zaatari, Ayman |
المؤلف | El Ballouli, Rim |
المؤلف | Elbassuoni, Shady |
المؤلف | El-Hajj, Wassim |
المؤلف | Hajj, Hazem |
المؤلف | Shaban, Khaled |
المؤلف | Habash, Nizar |
المؤلف | Yehya, Emad |
تاريخ الإتاحة | 2021-09-07T06:16:12Z |
تاريخ النشر | 2016 |
اسم المنشور | Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016 |
المصدر | Scopus |
الملخص | A significant portion of data generated on blogging and microblogging websites is non-credible as shown in many recent studies. To filter out such non-credible information, machine learning can be deployed to build automatic credibility classifiers. However, as in the case with most supervised machine learning approaches, a sufficiently large and accurate training data must be available. In this paper, we focus on building a public Arabic corpus of blogs and microblogs that can be used for credibility classification. We focus on Arabic due to the recent popularity of blogs and microblogs in the Arab World and due to the lack of any such public corpora in Arabic. We discuss our data acquisition approach and annotation process, provide rigid analysis on the annotated data and finally report some results on the effectiveness of our data for credibility classification. |
راعي المشروع | This work was made possible by grant NPRP 6-716-1-138 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. |
اللغة | en |
الناشر | European Language Resources Association (ELRA) |
الموضوع | Blogs Credibility Crowdsourcing |
النوع | Conference Paper |
الصفحات | 4396-4401 |
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