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A Generic Approach for Extracting Aspects and Opinions of Arabic Reviews

Published: 09 May 2016 Publication History

Abstract

New opportunities and challenges arise with the growing availability of online Arabic reviews. Sentiment analysis of these reviews can help the beneficiary by summarizing the opinions of others about entities or events. Also, for opinions to be comprehensive, analysis should be provided for each aspect or feature of the entity. In this paper, we propose a generic approach that extracts the entity aspects and their attitudes for reviews written in modern standard Arabic. The proposed approach does not exploit predefined sets of features, nor domain ontology hierarchy. Instead we add sentiment tags on the patterns and roots of an Arabic lexicon and used these tags to extract the opinion bearing words and their polarities. The proposed system is evaluated on the entity-level using two datasets of 500 movie reviews with accuracy 96% and 1000 restaurant reviews with accuracy 86.7%. Then the system is evaluated on the aspect-level using 500 Arabic reviews in different domains (Novels, Products, Movies, Football game events and Hotels). It extracted aspects, at 80.8% recall and 77.5% precision with respect to the aspects defined by domain experts.

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cover image ACM Other conferences
INFOS '16: Proceedings of the 10th International Conference on Informatics and Systems
May 2016
347 pages
ISBN:9781450340625
DOI:10.1145/2908446
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 May 2016

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Author Tags

  1. Arabic Sentiment Analysis
  2. Feature Extraction
  3. Opinion Mining
  4. Sentiment Classification

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  • (2024)A Spam Detecting Model Based on Basic ML Classifiers: Comparative Analysis via ABC Algorithm and Result GenerationBusiness Data Analytics10.1007/978-3-031-80778-7_23(313-324)Online publication date: 23-Dec-2024
  • (2023)A survey of sentiment analysis from film critics based on machine learning, lexicon and hybridizationNeural Computing and Applications10.1007/s00521-023-08359-635:13(9437-9461)Online publication date: 1-Mar-2023
  • (2022)A New Alignment Word-Space Approach for Measuring Semantic Similarity for Arabic TextInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.29703618:1(1-18)Online publication date: 24-Mar-2022
  • (2022)Sentiment Analysis of Arabic DocumentsResearch Anthology on Implementing Sentiment Analysis Across Multiple Disciplines10.4018/978-1-6684-6303-1.ch064(1237-1261)Online publication date: 10-Jun-2022
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