Using objective words in the reviews to improve the colloquial arabic sentiment analysis
One of the main difficulties in sentiment analysis of the Arabic language is the presence of the colloquialism. In this paper, we examine the effect of using objective words in conjunction with sentimental words on sentiment classification for the colloquial Arabic reviews, specifically Jordanian colloquial reviews. The reviews often include both sentimental and objective words, however, the most existing sentiment analysis models ignore the objective words as they are considered useless. In this work, we created two lexicons: the first includes the colloquial sentimental words and compound phrases, while the other contains the objective words associated with values of sentiment tendency based on a particular estimation method. We used these lexicons to extract sentiment features that would be training input to the Support Vector Machines (SVM) to classify the sentiment polarity of the reviews. The reviews dataset have been collected manually from JEERAN website. The results of the experiments show that the proposed approach improves the polarity classification in comparison to two baseline models, with accuracy 95.6%.
Code (0)
등록된 구현이 없습니다.
Tasks
Arabic Sentiment AnalysisGeneral ClassificationSentiment AnalysisSentiment ClassificationSimilar Papers 제목 키워드 기반
Idioms-Proverbs Lexicon for Modern Standard Arabic and Colloquial Sentiment Analysis
Although, the fair amount of works in sentiment analysis (SA) and opinion mining (OM) systems in the last decade and with respect to the performance of these systems, but it still not desired performance, especially for …
Opinion MiningSentenceSentiment AnalysisSentiment Analysis For Modern Standard Arabic And Colloquial
The rise of social media such as blogs and social networks has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has t…
Arabic Sentiment AnalysisNegationSentenceSentiment Analysis+1Developing LMF-XML Bilingual Dictionaries for Colloquial Arabic Dialects
The Linguistic Data Consortium and Georgetown University Press are collaborating to create updated editions of bilingual diction- aries that had originally been published in the 1960's for English-speaking learners of Mo…
ManagementTransforming Standard Arabic to Colloquial Arabic
Negation Handling in Machine Learning-Based Sentiment Classification for Colloquial Arabic
One crucial aspect of sentiment analysis is negation handling, where the occurrence of negation can flip the sentiment of a sentence and negatively affects the machine learning-based sentiment classification. The role of…
Arabic Sentiment AnalysisBIG-bench Machine LearningNegationSentence+2