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Hitham M. Abo Bakr
Zagazig University
Computer Science & IT Electrical & Electronics Engineering

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A Framework for Arabic Concept-Level Sentiment Analysis using SenticNet Hend G. Hassan; Hitham M. Abo Bakr; Ibrahim E. Ziedan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10752.049 KB) | DOI: 10.11591/ijece.v8i5.pp4015-4022

Abstract

Arabic Sentiment analysis research field has been progressing in a slow pace compared to English and other languages. In addition to that most of the contributions are based on using supervised machine learning algorithms while comparing the performance of different classifiers with different selected stylistic and syntactic features. In this paper, we presented a novel framework for using the Concept-level sentiment analysis approach which classifies text based on their semantics rather than syntactic features. Moreover, we provided a lexicon dataset of around 69 k unique concepts that covers multi-domain reviews collected from the internet. We also tested the lexicon on a test sample from the dataset it was collected from and obtained an accuracy of 70%. The lexicon has been made publicly available for scientific purposes.
Co-Authors Hend G. Hassan Ibrahim E. Ziedan