• العربية
    • English
  • English 
    • العربية
    • English
  • Login
Home
Publisher PoliciesTerms of InterestHelp Videos
Submit Thesis
IntroductionIUGSpace Policies
JavaScript is disabled for your browser. Some features of this site may not work without it.
View Item 
  •   Home
  • Faculty of Information Technology
  • Staff Publications- Faculty of Information Technology
  • View Item
  •   Home
  • Faculty of Information Technology
  • Staff Publications- Faculty of Information Technology
  • View Item

Please use this identifier to cite or link to this item:

http://hdl.handle.net/20.500.12358/27304
TitleLSTM-CNN Deep Learning Model for Sentiment Analysis of Dialectal Arabic
Title in ArabicLSTM-CNN Deep Learning Model for Sentiment Analysis of Dialectal Arabic
Abstract

In this paper we investigate the use of Deep Learning (DL) methods for Dialectal Arabic Sentiment Analysis. We propose a DL model that combines long-short term memory (LSTM) with convolutional neural networks (CNN). The proposed model performs better than the two baselines. More specifically, the model achieves an accuracy between 81% and 93% for binary classification and 66% to 76% accuracy for three-way classification. The model is currently the state of the art in applying DL methods to Sentiment Analysis in dialectal Arabic.

Authors
Abu Kwaik, Kathrein
Saad, Motaz K
Chatzikyriakidis, Stergios
Dobnik, Simon
TypeJournal Article
Date2019
LanguageEnglish
Subjects
deep learning
sentiment analysis
Published inArabic Language Processing: From Theory to Practice
SeriesVol. 1108
PublisherSpringer Science and Business Media LLC
Citation
Item linkItem Link
DOI10.1007/978-3-030-32959-4_8
ISSN18650929,18650937
ISBN9783030329587,9783030329594
License
Collections
  • Staff Publications- Faculty of Information Technology [192]
Files in this item
ICALP_Deep_Learning.pdf367.5Kb

The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Contact Us | Send Feedback
 

 

Browse

All of IUGSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsSupervisorsThis CollectionBy Issue DateAuthorsTitlesSubjectsSupervisors

My Account

LoginRegister

Statistics

View Usage Statistics

The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Contact Us | Send Feedback