A Combined CNN and LSTM Model for Arabic Sentiment Analysis

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Abstract

Deep neural networks have shown good data modelling capabilities when dealing with challenging and large datasets from a wide range of application areas. Convolutional Neural Networks (CNNs) offer advantages in selecting good features and Long Short-Term Memory (LSTM) networks have proven good abilities of learning sequential data. Both approaches have been reported to provide improved results in areas such image processing, voice recognition, language translation and other Natural Language Processing (NLP) tasks. Sentiment classification for short text messages from Twitter is a challenging task, and the complexity increases for Arabic language sentiment classification tasks because Arabic is a rich language in morphology. In addition, the availability of accurate pre-processing tools for Arabic is another current limitation, along with limited research available in this area. In this paper, we investigate the benefits of integrating CNNs and LSTMs and report obtained improved accuracy for Arabic sentiment analysis on different datasets. Additionally, we seek to consider the morphological diversity of particular Arabic words by using different sentiment classification levels.
Original languageEnglish
Title of host publicationCross Domain Conference for Machine Learning and Knowledge Extraction
Subtitle of host publicationCD-MAKE 2018
PublisherSpringer International Publishing
Pages179-191
Number of pages13
Volume11015
ISBN (Electronic)978-3-319-99740-7
ISBN (Print)978-3-319-99739-1
DOIs
Publication statusPublished - 24 Aug 2018
EventIFIP Cross Domain Conference for Machine Learning and Knowledge Extraction - Hamburg, Germany
Duration: 27 Aug 201830 Aug 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743

Conference

ConferenceIFIP Cross Domain Conference for Machine Learning and Knowledge Extraction
Abbreviated titleCD-MAKE 2018
CountryGermany
CityHamburg
Period27/08/1830/08/18

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Alayba, A., Palade, V., England, M., & Iqbal, R. (2018). A Combined CNN and LSTM Model for Arabic Sentiment Analysis. In Cross Domain Conference for Machine Learning and Knowledge Extraction: CD-MAKE 2018 (Vol. 11015, pp. 179-191). (Lecture Notes in Computer Science). Springer International Publishing. https://doi.org/10.1007/978-3-319-99740-7_12