Sentiment Analysis of Chinese E-commerce Reviews Based on BERT

Xie, Song and Cao, Jingjing and Wu, Zhou and Liu, Kai and Tao, Xiaohui ORCID: https://orcid.org/0000-0002-0020-077X and Xie, Haoran (2021) Sentiment Analysis of Chinese E-commerce Reviews Based on BERT. In: 18th IEEE International Conference on Industrial Informatics (INDIN 2020), 21 July - 23 July 2020, Warwick, United Kingdom.


Abstract

The popularity of the Internet has brought profound influence to electronic commerce. A kind of review-oriented consumption mode is gradually expanding in the market and consumers will refer to the reviews provided by consumers who bought the product in the past. How to accurately analyze users' sentiments from massive data of e-commerce reviews has become one of the key issues for e-commerce platforms. Current standard sentiment analysis classifies overall sentiment of e-commerce reviews without an extended description of the entity. We set up an optimized Aspect-based sentiment analysis (ABSA) that includes four elements: aspect, category, polarity, and opinion. Aiming at the above problems, this paper proposes a Chinese e-commerce reviews sentiment analysis algorithm based on BERT. By using pre-training model, we use the BIO(B-begin,I-inside,O-outside) data labeling pattern to label entities and study sentiment analysis by the annotation data. Experimental results on the Taobao cosmetics review datasets show that compared with the ordinary deep learning methods, our approach in the accuracy rate and the F1 score has significant improvement.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Date Deposited: 12 May 2022 01:20
Last Modified: 31 May 2022 00:11
Uncontrolled Keywords: e-commerce reviews; sentiment analysis; BERT
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460510 Recommender systems
46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460208 Natural language processing
46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460502 Data mining and knowledge discovery
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Socio-Economic Objectives (2020): 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences
22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220403 Artificial intelligence
Identification Number or DOI: https://doi.org/10.1109/INDIN45582.2020.9442190
URI: http://eprints.usq.edu.au/id/eprint/46215

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