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Improving Sentiment Analysis in Arabic Using Word Representation

Abdulaziz M. Alayba, Vasile Palade, Matthew England, Rahat Iqbal
2018 2018 IEEE 2nd International Workshop on Arabic and Derived Script Analysis and Recognition (ASAR)  
The complexities of Arabic language in morphology, orthography and dialects makes sentiment analysis for Arabic more challenging.  ...  available Arabic language health sentiment dataset [1]  ...  applied morphology-based and lexical features for Arabic sentiment analysis; [12] improved the performance of sentiment analysis for Arabic, using different techniques like stemming, POS and expanding  ... 
doi:10.1109/asar.2018.8480191 dblp:conf/asar/AlaybaPEI18 fatcat:f6axamz655dbfbjy5xvypydtpe

Semantic Sentiment Analysis of Arabic Texts

Sana Alowaidi, Mustafa Saleh, Osama Abulnaja
2017 International Journal of Advanced Computer Science and Applications  
In this work, a semantic Arabic Twitter Sentiment Analysis (ATSA) model is developed based on supervised machine learning (ML) approaches and semantic analysis.  ...  The experimental results indicate that using concepts features improves the performance of the ATSA model compared with the basic BoW representation.  ...  This paper presents an Arabic Twitter Sentiment Analysis (ATSA) model, a semantic sentiment analysis model for Arabic Twitter data using ML approaches.  ... 
doi:10.14569/ijacsa.2017.080234 fatcat:62jqjgkfdfh6xe3ajtbcqezmgq

hULMonA: The Universal Language Model in Arabic

Obeida ElJundi, Wissam Antoun, Nour El Droubi, Hazem Hajj, Wassim El-Hajj, Khaled Shaban
2019 Proceedings of the Fourth Arabic Natural Language Processing Workshop  
We then conduct a benchmark study to evaluate both ULM successes with Arabic sentiment analysis.  ...  Experiment results show that the developed hULMonA and multi-lingual ULM are able to generalize well to multiple Arabic data sets and achieve new state of the art results in Arabic Sentiment Analysis for  ...  The use of these word embeddings was shown to improve the state-ofthe-are results in six NLP tasks such as sentiment analysis and question answering.  ... 
doi:10.18653/v1/w19-4608 dblp:conf/wanlp/ElJundiADHES19 fatcat:oe6climpnrhyfnusyyt6ngbn3y

SMARTies: Sentiment Models for Arabic Target entities

Noura Farra, Kathy McKeown
2017 Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers  
We consider entity-level sentiment analysis in Arabic, a morphologically rich language with increasing resources.  ...  We achieve significant improvements over multiple baselines, demonstrating that the use of specific morphological representations improves the performance of identifying both important targets and their  ...  Acknowledgments This work was supported in part by grant NPRP 6-716-1-138 from the Qatar National Research Fund, by DARPA DEFT grant FA8750-12-2-0347 and by DARPA LORELEI grant HR0011-15-2-0041.  ... 
doi:10.18653/v1/e17-1094 dblp:conf/eacl/McKeownF17 fatcat:sosk53jl75gxdetcwliixyvz5a

SMARTies: Sentiment Models for Arabic Target Entities [article]

Noura Farra, Kathleen McKeown
2017 arXiv   pre-print
We consider entity-level sentiment analysis in Arabic, a morphologically rich language with increasing resources.  ...  We achieve significant improvements over multiple baselines, demonstrating that the use of specific morphological representations improves the performance of identifying both important targets and their  ...  Acknowledgments This work was supported in part by grant NPRP 6-716-1-138 from the Qatar National Research Fund, by DARPA DEFT grant FA8750-12-2-0347 and by DARPA LORELEI grant HR0011-15-2-0041.  ... 
arXiv:1701.03434v1 fatcat:r6dq2xsokjhpfl4yonnkminqia

A Deep Learning Approach Combining CNN and Bi-LSTM with SVM Classifier for Arabic Sentiment Analysis

Omar Alharbi
2021 International Journal of Advanced Computer Science and Applications  
Keywords-Sentiment analysis; Arabic sentiment analysis; deep learning approach; convolutional neural network CNN; bidirectional long short-term memory Bi-LSTM; support vector machine; SVM 165 | P a g e  ...  Deep learning models have recently been proven to be successful in various natural language processing tasks, including sentiment analysis.  ...  This approach has improved the stateof-the-art in many SA tasks, including sentiment classification, opinion extraction, and fine-grained sentiment analysis [10] .  ... 
doi:10.14569/ijacsa.2021.0120618 fatcat:okprmey4ibe7rjnrmvewojzjay

A study of the effects of preprocessing strategies on sentiment analysis for Arabic text

Rehab Duwairi, Mahmoud El-Orfali
2014 Journal of information science  
This paper deals with sentiments analysis in Arabic text from three perspectives. Firstly, several alternatives of text representation were investigated.  ...  In particular, the effects of stemming, feature correlation, and n-gram models for Arabic text on sentiment analysis were investigated.  ...  For example, the work reported here deals with sentiment analysis at the review or document level. A useful extension would be to find the sentiment at the sentence level.  ... 
doi:10.1177/0165551514534143 fatcat:zcj66yfyd5a5lfyoa3jy6g3bui

Learning Word Representations for Tunisian Sentiment Analysis [article]

Abir Messaoudi and Hatem Haddad and Moez Ben HajHmida and Chayma Fourati and Abderrazak Ben Hamida
2020 arXiv   pre-print
In this paper, we focus on the Tunisian dialect sentiment analysis used on social media. Most of the previous work used machine learning techniques combined with handcrafted features.  ...  In this paper, we explore the importance of various unsupervised word representations (word2vec, BERT) and we investigate the use of Convolutional Neural Networks and Bidirectional Long Short-Term Memory  ...  Initial Representations In order to evaluate Tunisian Romanized sentiment analysis, three initial representation were used: word2vec, frWaC and multilingual BERT (M-BERT). • Word2vec [20] : Word-level  ... 
arXiv:2010.06857v1 fatcat:ctpvww463rbtxh43qjbwvkioei

Fine-Grained Sentiment Analysis of Arabic COVID-19 Tweets Using BERT-Based Transformers and Dynamically Weighted Loss Function

Nora Alturayeif, Hamzah Luqman
2021 Applied Sciences  
We also show how the textual representation of emojis can boost the performance of sentiment analysis.  ...  We employ two transformer-based models for fine-grained sentiment detection of Arabic tweets, considering that more than one emotion can co-exist in the same tweet.  ...  Therefore, contextual techniques learn different representations for polysemous words [53] . In this work, we utilized both embedding representations for Arabic sentiment analysis.  ... 
doi:10.3390/app112210694 fatcat:2t7fqfmzr5ezvhr2ytcpynkliy

ArCAR: A Novel Deep Learning Computer-Aided Recognition for Character-Level Arabic Text Representation and Recognition

Abdullah Y. Muaad, Hanumanthappa Jayappa, Mugahed A. Al-antari, Sungyoung Lee
2021 Algorithms  
Meanwhile, the ArCAR performs well for Arabic sentiment analysis, achieving the best performance using the hotel Arabic reviews dataset (HARD) balance dataset in terms of overall accuracy and F1-score  ...  The ArCAR system is validated over 5-fold cross-validation tests for two applications: Arabic text document classification and Arabic sentiment analysis.  ...  In 2020, Elfaik et al. used the Arabic text representation based on the word level and investigated the bidirectional LSTM network (BiLSTM) to enhance the Arabic sentiment analysis [48] .  ... 
doi:10.3390/a14070216 fatcat:ae5kraaz4nacxlj2pt34cbbtii

Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification

Abdelghani Dahou, Shengwu Xiong, Junwei Zhou, Mohamed Houcine Haddoud, Pengfei Duan
2016 International Conference on Computational Linguistics  
In this paper, a scheme of Arabic sentiment classification, which evaluates and detects the sentiment polarity from Arabic reviews and Arabic social media, is studied.  ...  Moreover, a convolutional neural network trained on top of pretrained Arabic word embeddings is used for sentiment classification to evaluate the quality of these word embeddings.  ...  In particular, we perform a comprehensive analysis to train and evaluate word representations using CBOW and Skip-Gram models, with the goal of generating a better quality representations for Arabic sentiment  ... 
dblp:conf/coling/DahouXZHD16 fatcat:ybf37cufknettk7ncgfjsaxnau

LSIS at SemEval-2017 Task 4: Using Adapted Sentiment Similarity Seed Words For English and Arabic Tweet Polarity Classification

Amal Htait, Sébastien Fournier, Patrice Bellot
2017 Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)  
We present, in this paper, our contribution in SemEval2017 task 4 : "Sentiment Analysis in Twitter", subtask A: "Message Polarity Classification", for English and Arabic languages.  ...  Our tests, using these seed words, show significant improvement in results compared to the use of Turney and Littman's (2003) seed words, on polarity classification of tweet messages.  ...  Arabic seed words The Arabic language's experiences, in lexicalbased sentiment analysis, were mostly oriented to sentiment lexicons than to seed words.  ... 
doi:10.18653/v1/s17-2120 dblp:conf/semeval/HtaitFB17 fatcat:3ypr2u4oj5hcxilfk7nu4cm7ga

Arabic dialect sentiment analysis with ZERO effort. \\ Case study: Algerian dialect

Imane Guellil, Marcelo Mendoza, Faical Azouaou
2020 Inteligencia Artificial  
We use a state-of-the-art system and propose a new deep learning architecture for automatically classify the sentiment of Arabic dialect (Algerian dialect).  ...  We apply this idea on Algerian dialect, which is a Maghrebi Arabic dialect that suffers from limited available tools and other handling resources required for automatic sentiment analysis.  ...  Furthermore, to use a BOW representation in sentiment analysis, an appropriate word feature extraction process is required [2, 8] .  ... 
doi:10.4114/intartif.vol23iss65pp124-135 fatcat:f6tbt6y3erdnxbv27khbvygiw4

Document Embeddings for Arabic Sentiment Analysis

Amira Barhoumi, Yannick Estève, Chafik Aloulou, Lamia Hadrich Belguith
2017 Conference on Language Processing and Knowledge Management  
This paper focuses on Arabic sentiment analysis and investigates the use of paragraph vector within a machine learning techniques to determine the polarity of a given text.  ...  Paragraph vector has been recently proposed to learn embeddings which are leveraged for English sentiment analysis.  ...  The Doc2vec representations were used for English sentiment analysis by [15] .  ... 
dblp:conf/lpkm/BarhoumiEAB17 fatcat:nr4jxaq5ovc2rpvs56wrhdacwu

Arabic aspect based sentiment classification using BERT [article]

Mohammed M.Abdelgwad
2021 arXiv   pre-print
Most previous Arabic research has relied on deep learning models that depend primarily on context-independent word embeddings (e.g.word2vec), where each word has a fixed representation independent of its  ...  Aspect-based sentiment analysis(ABSA) is a textual analysis methodology that defines the polarity of opinions on certain aspects related to specific targets.  ...  Using word embedding or distributed representations enhances neural network efficiency and improves the performance of Deep Learning (DL) models, therefore, it has been applied as a preliminary layer in  ... 
arXiv:2107.13290v3 fatcat:hjkmmmo2y5dstoc64xighnqi2y
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