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Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach
المؤلف
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 16، العدد 6 (30 نوفمبر/تشرين الثاني 2019)، ص ص. 995-1002، 8ص.
الناشر
تاريخ النشر
2019-11-30
دولة النشر
الأردن
عدد الصفحات
8
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
اللغة العربية وآدابها
الموضوعات
الملخص EN
Arab Internet users tend to use dialectical words to express how they feel about products, services, and places.
Although, dialects in Arabic derived from the formal Arabic language, it differs in several aspects.
In general, Arabic sentiment analysis recently attracted lots of researchers’ attention.
A considerable amount of research has been conducted in Modern Standard Arabic (MSA), but little work has focused on dialectal Arabic.
The presence of the dialect in the Arabic texts made Arabic sentiment analysis is a challenging issue, due to it usually does not follow specific rules in writing or speaking system.
In this paper, we implement a semi-supervised approach for sentiment polarity classification of dialectal reviews with the presence of Modern Standard Arabic (MSA).
We combined dialectal sentiment lexicon with four classifying learning algorithm to perform the polarity classification, namely Support Vector Machines (SVM), Naïve Bayes (NB), Random Forest, and K-Nearest Neighbor (K-NN).
To select the features with which the classifiers can perform the best, we used three feature evaluation methods, namely, Correlation-based Feature Selection, Principal Components Analysis, and SVM Feature Evaluation.
In the experiment, we applied the approach to a data set which was manually collected.
The experimental results show that the approach yielded the highest classification accuracy using SVM algorithm with 92.3 %.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
al-Harbi, Umar A.. 2019. Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach. The International Arab Journal of Information Technology،Vol. 16, no. 6, pp.995-1002.
https://search.emarefa.net/detail/BIM-915142
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
al-Harbi, Umar A.. Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach. The International Arab Journal of Information Technology Vol. 16, no. 6 (Nov. 2019), pp.995-1002.
https://search.emarefa.net/detail/BIM-915142
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
al-Harbi, Umar A.. Classifying sentiment of dialectal Arabic reviews : a semi-supervised approach. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 6, pp.995-1002.
https://search.emarefa.net/detail/BIM-915142
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 1001-1002
رقم السجل
BIM-915142
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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