References
- P. Natalie, and T. Yue, T. (2020). "What about WhatsApp? A systematic review of WhatsApp and its role in civic and political engagement," First Monday, vol. 25, 2020, [https:// doi.org/ 10.5210 / fm. v25i12.10417] https://doi.org/10.5210/fm.v25i12.10417
- H. Tankovska, "Daily active users of WhatsApp status 2019," Statistica, 2021, [Retrieved on Jan 18, 2021]
- I. Shreen, and R. Tariq, "Identify theft and social media," International Journal of Computer Science and Network Security, vol. 18, pp. 43-55, 2018
- P. Poonam, K. Krishan, S. Bharanidharan, C. Kheng, "A theoretical review of social media usage by cybercriminals, "in Conference on Computer Communication and Informatics, 2017, India
- A. Abbe, C. Grouin, P. Zweigenbaum, B. Falissard, "Text mining applications in psychiatry: a systematic literature review," International Journal of Methods in Psychiatric Research, 25, pp. 86-100. 2016 https://doi.org/10.1002/mpr.1481
- H. Fatma, M. Masnizah, A. Zahra, and A. Jowan, "Authorship attribution of short historical arabic texts using stylometric features and a KNN classifier withlLimited training data," Journal of Computer Science, vol. 16, pp. 1334-1345, 2020 https://doi.org/10.3844/jcssp.2020.1334.1345
- A.-B. Jafar, T. Bashar, A.-A. Mahmoud, and B. Zaqaibeh, "Using big data analytics for authorship authentication of arabic tweets," in 8th IEEE/ACM International Conference on Utility and Cluod Computing, 2015, Cyprus
- B. Mariam, E.Wael, T. Sara, and H. Amjad, "Sentiment classification techniques for arabic language: a survey," in 7th International Conference on Information and Communication Systems, 2016, Jordan
- S. Amira, and R. Ahmed, "Sentence-Level Arabic Sentiment Analysis," in International Symposium on Collaboration, Social Computing, New Media and Networks (SoMNet2012), Cairo
- A. -f. Ahmed, R. Mohammed, and M. Bellafkih,."Machine learning for authorship attribution in arabic poetry, " International Journal of Future Computer and Communication, vol. 6, pp. 42-46, 2017 https://doi.org/10.18178/ijfcc.2017.6.2.486
- A. El-Halees, "Opinion mining from arabic comparative sentences, " in International Arab Conference on Information Technology, 2012, Jordan
- A. Mohammad, I. Norisma, M. Rohana, J. Salinah, T. Dirk, and A. Gani, "Hadith data mining and classification: a comparative analysis, " Artificial Inteliigence Review, vol. 46, pp. 113-128, 2016 https://doi.org/10.1007/s10462-016-9458-x
- A. Muhammad, A. Tanvir, S. Fahad, and I. Muhammad, "Feature extraction based text classification using k-nearest neighbor algorithm," Internationla Journal of Computer Science and Network Security, vol. 18, pp. 95-101, 2018
- R. Oppliger, "Automatic authorship attribution based on character n-grams in Swiss German," in 13th Conference on Natural Language Processing (KONVENS), 2016, Germany
- S. Abhay, N. Ananya, and R. Reetika, "An investigation of supervised learning methods for authorship," ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 1, pp. 1-11, 2018
- A. Lama, S. Mostafa, and E. Fathy, "Arabic blogging Sentiment Analysis," La Pensee, vol. 76, 2016
- W. Koehrsen, "Overfitting vs. Underfitting: A Complete Example," [Retrieved from towardsdatascience: https://towardsdatascience.com/overfitting-vsunderfitting-a-completeexample-d05dd7e19765]
- J. Chen, Y. Hu, J. Liu, Y. Xiao, and H. Jiang, "Deep Short Text Classification with Knowledge Powered Attention," in Proceedings of the AAAI Conference on Artificial Intelligence. 33. 2019