research-article

Two New Large Corpora for Vietnamese Aspect-based Sentiment Analysis at Sentence Level

Authors:

Ngan Luu-Thuy Nguyen,

Tri Minh Truong,

Duy Tin VoAuthors Info & Claims

Transactions on Asian and Low-Resource Language Information Processing, Volume 20, Issue 4

Article No.: 62, Pages 1 - 22

https://doi.org/10.1145/3446678

Published: 26 May 2021 Publication History

Abstract

Aspect-based sentiment analysis has been studied in both research and industrial communities over recent years. For the low-resource languages, the standard benchmark corpora play an important role in the development of methods. In this article, we introduce two benchmark corpora with the largest sizes at sentence-level for two tasks: Aspect Category Detection and Aspect Polarity Classification in Vietnamese. Our corpora are annotated with high inter-annotator agreements for the restaurant and hotel domains. The release of our corpora would push forward the low-resource language processing community. In addition, we deploy and compare the effectiveness of supervised learning methods with a single and multi-task approach based on deep learning architectures. Experimental results on our corpora show that the multi-task approach based on BERT architecture outperforms the neural network architectures and the single approach. Our corpora and source code are published on this footnoted site.¹

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Cited By

Aliyu YSarlan AUsman Danyaro KRahman AAbdullahi M(2024)Sentiment Analysis in Low-Resource Settings: A Comprehensive Review of Approaches, Languages, and Data SourcesIEEE Access10.1109/ACCESS.2024.339863512(66883-66909)Online publication date: 2024
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Aziz KAhmed NHadi HYusufu AAlshara MJaved YJi D(2024)Enhanced UrduAspectNet: Leveraging Biaffine Attention for superior Aspect-Based Sentiment AnalysisJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2024.10222136:9(102221)Online publication date: Nov-2024
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Index Terms

Two New Large Corpora for Vietnamese Aspect-based Sentiment Analysis at Sentence Level
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 20, Issue 4

July 2021

419 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3465463

Editor:
Imed Zitouni
Google, USA

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Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 26 May 2021

Accepted: 01 January 2021

Revised: 01 December 2020

Received: 01 February 2020

Published in TALLIP Volume 20, Issue 4

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Vietnam National University HoChiMinh City (VNU-HCM)

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Cited By

Aliyu YSarlan AUsman Danyaro KRahman AAbdullahi M(2024)Sentiment Analysis in Low-Resource Settings: A Comprehensive Review of Approaches, Languages, and Data SourcesIEEE Access10.1109/ACCESS.2024.339863512(66883-66909)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3398635
Aziz KAhmed NHadi HYusufu AAlshara MJaved YJi D(2024)Enhanced UrduAspectNet: Leveraging Biaffine Attention for superior Aspect-Based Sentiment AnalysisJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2024.10222136:9(102221)Online publication date: Nov-2024
https://doi.org/10.1016/j.jksuci.2024.102221
Le HDo TNguyen MTran HPham TNguyen NNguyen V(2024)Predictive model for customer satisfaction analytics in E-commerce sector using machine learning and deep learningInternational Journal of Information Management Data Insights10.1016/j.jjimei.2024.1002954:2(100295)Online publication date: Nov-2024
https://doi.org/10.1016/j.jjimei.2024.100295
Khang VThuan N(2024)Combining the 1D CNN Model and Transfer Learning Model in Analyzing Learner EmotionsFuture Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications10.1007/978-981-96-0437-1_23(314-328)Online publication date: 27-Nov-2024
https://doi.org/10.1007/978-981-96-0437-1_23
Van Thin DHao DNguyen N(2023)A Systematic Literature Review on Vietnamese Aspect-based Sentiment AnalysisACM Transactions on Asian and Low-Resource Language Information Processing10.1145/361022622:8(1-28)Online publication date: 24-Aug-2023
https://dl.acm.org/doi/10.1145/3610226
Thin DHao DNguyen N(2023)A Study of Vietnamese Sentiment Classification with Ensemble Pre-Trained Language ModelsVietnam Journal of Computer Science10.1142/S219688882350017311:01(137-165)Online publication date: 7-Dec-2023
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Guven Z(2022)The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment AnalysisACM Transactions on Asian and Low-Resource Language Information Processing10.1145/355789222:2(1-16)Online publication date: 27-Dec-2022
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Van Thin DHao DHoang VNguyen N(2022)Investigating Monolingual and Multilingual BERT Models for Vietnamese Aspect Category Detection2022 RIVF International Conference on Computing and Communication Technologies (RIVF)10.1109/RIVF55975.2022.10013792(130-135)Online publication date: 20-Dec-2022
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Van Thin DHao DNguyen N(2022)An Effective Contextual Language Ensemble Model for Vietnamese Aspect-based Sentiment Analysis2022 9th NAFOSTED Conference on Information and Computer Science (NICS)10.1109/NICS56915.2022.10013429(30-34)Online publication date: 31-Oct-2022
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Doan ALuu S(2022)Improving Sentiment Analysis By Emotion Lexicon Approach on Vietnamese Texts2022 International Conference on Asian Language Processing (IALP)10.1109/IALP57159.2022.9961318(39-44)Online publication date: 27-Oct-2022
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