A Framework for Arabic Concept-Level Sentiment Analysis using SenticNet

Hend G. Hassan, Hitham M. Abo Bakr, Ibrahim E. Ziedan

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.

Keywords


arabic reviews; opinion mining; sentiment analysis; sentiment lexicons

Full Text:

PDF


DOI: http://doi.org/10.11591/ijece.v8i5.pp4015-4022
Total views : 603 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.