Saud Alotaibi

Work place: Umm Alqura Univerisity, Al Taif Road, Makkah and 24382, Saudi Arabia



Research Interests:


Saud Alotaibi received his Bachelor of Computer Science degree from King Abdul Aziz University, 2000. He worked as an Assistant Lecturer at Umm Alqura University, Makkah, Saudi Arabia (Jan, 2001). He also earned his Master of Computer Science degree from King Fahd University, Dhahran, May 2008. Following this, Saud worked as the Deputy of the ITCentre for E-Government Affairs in Jan 2009, (Umm Alqura University). In 2015, Saud completed his Ph.D. degree in Computer Science from Colorado State University, Fort Collins, US. Currently, he works at Umm Alqura University, as an Assistant Professor.

Author Articles
Word Clustering as a Feature for Arabic Sentiment Classification

By Saud Alotaibi Charles Anderson

DOI:, Pub. Date: 8 Jan. 2017

Rich morphology language, such as Arabic, requires more investigation and methods targeted toward improving the sentiment analysis task. An example of external knowledge that may provide some semantic relationships within the text is the word clustering technique. This article demonstrates the ongoing work that utilizes word clustering when conducting Arabic sentiment analysis. Our proposed method employs supervised sentiment classification by enriching the feature space model with word cluster information. In addition, the experiments and evaluations that were conducted in this study demonstrated that by combining the clustering feature with sentiment analysis for Arabic, this improved the performance of the classifier.

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