ABSTRACT
Aspect-based sentiment classification is an important task in natural language processing research, and in response to the fact that most studies at this stage ignore the influence of contextual semantic information on the sentiment polarity of aspect words, our model proposed in this paper combines local aspect word feature extraction and global contextual semantic information extraction based on Bi-directional Long Short-Term Memory (BiLSTM), and after a multi-headed attention mechanism to enhance the local aspect word sentiment representation. Comparative experiments were conducted on the restaurant and laptop datasets of the SEMEVAL2014 evaluation task. The experimental results show that the model proposed in this paper achieves good classification results in the aspect-level sentiment analysis task of text reviews. The method provides a new idea for ABSA task development.
- Pontiki, M.; Galanis, D.; Pavlopoulos, J.; Papageorgiou, H.;Androutsopoulos, I.; and Manandhar, S. 2014. Semeval 2014 task 4:Google Scholar
- Aspect based sentiment analysis. In SemEval@COLING 2014, 27–35.Google Scholar
- Shinhyeok Oh1, Dongyub Lee2*, Taesun Whang Deep Context-and Relation-Aware Learningfor Aspect-based Sentiment Analysis,arXiv:2016.038.6v1.2021.Google Scholar
- Zeng B, Yang H, Xu R, Lcf: A local context focus mechanism for aspect-based sentiment classification[J]. Applied Sciences, 2019, 9(16): 3389.Google ScholarCross Ref
- Wu Z, Ong D C. Context-guided bert for targeted aspect-based sentiment analysis[C]//Proceedings of the AAAI Conference on Artificial Intelligence, Online, Feb 2-9, 2021, 35(16): 14094- 14102. Hochreiter S, Schmidhuber J.Long short-term memory[J].Neural Computation, 1997, 9(8):1735-1780.Google Scholar
- WU B R, QIAO H, JIA Y F, Sentiment Analysis of Mid length Microblog Based on Capsule Network[J]. Journal of Signal Processing,2022,38(8):1632-1641. DOI: 10.16798/j. issn.1003-0530.2022.08.008.Google ScholarCross Ref
- TANG D Y, QIN B, FENG X C, Effective LSTMs for target-dependent sentiment classification[C]//Proceedings of the 26th International Conference on Computational Linguistics: Technical Papers, 2016: 3298-3307Google Scholar
- Hong Chen, Yan Yang, Shengdong Du. User comment aspect level sentiment analysis research[J]. Computer science and Exploration, 2021, 15(3): 478-485.Google Scholar
- Zhidong Xu, Binyang Chen, Xiao Wang. Research on aspect level emotion classification based on capsule network[J]. Journal of Intelligent Science and Technology, 2020, 2(3): 284-292Google Scholar
- TIN SONG, Zhanwei Chen, Haifeng Yang. Aspect emotion analysis based on hierarchical attention network[J]. Big data, 2020, 6(5): 82-91.Google Scholar
- Peng, H., Ma, Y., Li, Y., Cambria, E., 2018. Learning multi-grained aspect target sequence for chinese sentiment analysis. Knowledge-Based Systems 148, 167–176. doi:10.1016/j.knosys.2018.02.034.Google ScholarCross Ref
- Chen, F., Huang, Y., 2019. Knowledge-enhanced neural networks for sentiment analysis of chinese reviews. Neurocomputing 368, 51 – 58.Google Scholar
- Liu, N., Shen, B., 2019. Aspect-based sentiment analysis with gated alternate neural network. Knowledge-Based Systems , 105010.Google Scholar
- Zeng, Z., Ma, J., Chen, M., Li, X., 2019b. Joint learning for aspect category detection and sentiment analysis in chinese reviews, in: China Conference on Information Retrieval, Springer. pp. 108–120.Google ScholarDigital Library
- WANG Y Q, HUANG M L, ZHU X Y, Attention-based LSTM for aspect-level sentiment classification[C]//Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Stroudsburg: Association for Computational Linguistics, 2016: 606-615.Google Scholar
- Ma, D., Li, S., Zhang, X. & Wang, H. Interactive attention networks for aspect-level sentiment classification[C]. Proceedings of the twenty-sixth international joint conference on artificial intelligence.2017:4069–4074.Google Scholar
- Chi Sun, Luyao Huang, Xipeng Qiu*. Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence.[C]//Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics :Human Language Technologies,2019:380-385Google Scholar
- LI Pan,WU Yadong,CHU QikaiFU,Chaoshuai,ZHANG Guiyu,et al.Aspect-based sentiment analysis of long text based on BERT and memory network [J]. Transducer and Microsystem Technologies,2022(2):118-122.Google Scholar
Index Terms
- Fusion Local and Global Aspect-based Sentiment Analysis
Recommendations
Sentence compression for aspect-based sentiment analysis
Sentiment analysis, which addresses the computational treatment of opinion, sentiment, and subjectivity in text, has received considerable attention in recent years. In contrast to the traditional coarse-grained sentiment analysis tasks, such as ...
Modeling multi-aspects within one opinionated sentence simultaneously for aspect-level sentiment analysis
AbstractAspect-level sentiment analysis aims at inferring the sentiment polarity with respect to a specific aspect term in an opinionated text, and has attracted a surge of active research interest in the research community. Years of research ...
Highlights- Content and position attention are involved to measure the influence of each context word on a given aspect.
Aspect and sentiment unification model for online review analysis
WSDM '11: Proceedings of the fourth ACM international conference on Web search and data miningUser-generated reviews on the Web contain sentiments about detailed aspects of products and services. However, most of the reviews are plain text and thus require much effort to obtain information about relevant details. In this paper, we tackle the ...
Comments