Stacking BERT based Models for Arabic Sentiment Analysis

Hasna Chouikhi; Hamza Chniter; Fethi Jarray; Fethi Jarray

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Paper

Stacking BERT based Models for Arabic Sentiment Analysis

Topics: Natural Language Processing

In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 0IC3K, 144-150, 2021

Authors: Hasna Chouikhi ¹ ; Hamza Chniter ² and Fethi Jarray ^{2

;

1}

Affiliations: ¹ LIMTIC Laboratory, UTM University, Tunisia ; ² Higher Institute of Computer Science of Medenine, Tunisia

Keyword(s): Arabic Sentiment Analysis, BERT Models, Stacking Approach, Large Scale Dataset.

Abstract: Recently, transformer-based models showed great success in sentiment analysis and were considered as the state-of-the-art model for various languages. However, the accuracy of Arabic sentiment analysis still needs improvements. In this work, we proposed a stacking architecture of Arabic sentiment analysis by combing different BERT models. We also create a large-scale dataset of Arabic sentiment analysis by merging small publicly available datasets. The experimental study proves the efficiency of the proposed approach in terms of classification accuracy compared to single model architecture.

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Paper citation in several formats:

Chouikhi, H.; Chniter, H. and Jarray, F. (2021). Stacking BERT based Models for Arabic Sentiment Analysis. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KEOD; ISBN 978-989-758-533-3; ISSN 2184-3228, SciTePress, pages 144-150. DOI: 10.5220/0010648400003064

@conference{keod21,
author={Hasna Chouikhi. and Hamza Chniter. and Fethi Jarray.},
title={Stacking BERT based Models for Arabic Sentiment Analysis},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KEOD},
year={2021},
pages={144-150},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010648400003064},
isbn={978-989-758-533-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KEOD
TI - Stacking BERT based Models for Arabic Sentiment Analysis
SN - 978-989-758-533-3
IS - 2184-3228
AU - Chouikhi, H.
AU - Chniter, H.
AU - Jarray, F.
PY - 2021
SP - 144
EP - 150
DO - 10.5220/0010648400003064
PB - SciTePress