Baheta: Balanced and Unbalanced Dataset in Arabic Clickbait Detection Using a Deep Learning Model (LSTM)

Author:

Alharbi Batool,Alhanaya Razan,Alqarawi Deem,Alnejaidi Ruwaidah

Publisher

Springer Nature Switzerland

Reference16 articles.

1. Satista. Number of Internet and Social Media Users Worldwide as of January 2023. [January 2023 May 2023]; Available from: https://www.statista.com/statistics/617136/digital-population-worldwide/

2. D. Ruby, 69+ Fake News Statistics Revealed For 2023 (Updated). [April 17, 2023 May 2023]; Available from: https://www.demandsage.com/fake-news-statistics/

3. P. Ongsulee, Artificial intelligence, machine learning and deep learning, in 2017 15th International Conference on ICT and Knowledge Engineering (ICT&KE), (IEEE, 2017)

4. M. Al-Sarem et al., An improved multiple features and machine learning-based approach for detecting Clickbait news on social networks. Appl. Sci. 11(20), 9487 (2021)

5. M. Yaseen, Arabic Fake News Dataset (AFND). 2022. Available from: https://www.kaggle.com/datasets/murtadhayaseen/arabic-fake-news-dataset-afnd?resource=download

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