A New Approach for Author Profiling and Identification of Deception in Texts
Hamada A. Nayel
International Journal of Computational Linguistics Research, Vol. 11, No. 2, 2020.
DOI: https://doi.org/10.6025/jcl/2020/11/2/73-79
Link: http://www.dline.info/jcl/fulltext/v11n2/jclv11n2_3.pdf
Abstract:
In this paper, we describe the methods and experiments that have been used in development of our system for Author Profiling and Deception Detection in Arabic shared task. There are two tasks, Author Profiling in Arabic Tweets and Deception Detection in Arabic Texts. We have submitted three runs for each task. The proposed system depends on classical machine learning approaches namely Linear Classier, Support Vector Machine and Multilayer Perceptron Classier. Bag-of- Word with range of n-grams model has been used for feature extraction. Our submissions for the first task achieved the second, seventh and third ranks. For the second task, one of our submissions outperformed all other submissions developed by other teams.