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基于LSTM的文本情感分析方法
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Abstract:
随着互联网的发展和电子商务的兴起，人们通过各种社交、电商平台发表自己的看法与见解，从这些用户评论数据中准确地挖掘出有用的信息是当前的研究热点。针对网络中的各类文本评论数据，本文基于深度学习的方法对这些数据进行情感分析，采用长短期记忆(Long Short-Term Memory, LSTM)神经网络模型构建情感分类器，对文本的情感倾向进行预测与分类。实验表明基于LSTM的情感分析方法可以很好地解决长距离依赖问题，具有较好的分类效果。
With the development of the Internet and the rise of e-commerce, people express their views and opinions through various social and e-commerce platforms. It is a challenging issue to accurately mine useful information from user comment data. For all kinds of text comment data in the network, sentiment of the comment data is analyzed in this paper through deep learning. The Long Short-Term Memory (LSTM) neural network model is used to construct a sentiment classifier to predict and classify the sentiment tendency of the text. The experimental results show that the sentiment analysis method based on LSTM can solve the problem of long-distance dependence and has a good classification effect.
| [1] | Studiawan, H., Sohel, F. and Payne, C. (2020) Anomaly Detection in Operating System Logs with Deep Learning-based Sentiment Analysis. IEEE Transactions on Dependable and Secure Computing, 18, 2136-2148.
https://doi.org/10.1109/TDSC.2020.3037903 |
| [2] | 张军阳, 王慧丽, 郭阳, 等. 深度学习相关研究综述[J]. 计算机应用研究, 2018, 35(7): 1921-1928+1936. |
| [3] | 王天笑. 自然语言处理的现状研究与未来发展初探[J]. 中国科技纵横, 2017, 1(2): 196-197. |
| [4] | 刘爽, 赵景秀, 杨红亚, 等. 文本情感分析综述[J]. 软件导刊, 2018, 17(6): 1-4+21. |
| [5] | Zhai, G., Yang, Y., Wang, H., et al. (2020) Multi-Attention Fusion Modeling for Sentiment Analysis of Educational Big Data. Big Data Mining and Analytics, 3, 311-319. https://doi.org/10.26599/BDMA.2020.9020024 |
| [6] | 王根生, 黄学坚. 基于Word2vec和改进型TF-IDF的卷积神经网络文本分类模型[J]. 小型微型计算机系统, 2019, 40(5): 1120-1126. |
| [7] | Singh, L.G. and Singh, S.R. (2020) Empirical Study of Sentiment Analysis Tools and Techniques on Societal Topics. Journal of Intelligent Information Systems, 56, 379-407. https://doi.org/10.1007/s10844-020-00616-7 |
| [8] | Kim, Y. (2014) Convolutional Neural Networks for Sentence Classification. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, Doha, October 2014, 1746-1751.
https://doi.org/10.3115/v1/D14-1181 |
| [9] | Sun, J., Han, P., Cheng, Z., et al. (2020) Transformer Based Multi-Grained Attention Network for Aspect-Based Sentiment Analysis. IEEE Access, 8, 211152-211163. https://doi.org/10.1109/ACCESS.2020.3039470 |
| [10] | 梁军, 柴玉梅, 原慧斌, 等. 基于极性转移和 LSTM 递归网络的情感分析[J]. 中文信息学报, 2015, 29(5): 152-159. |
| [11] | 杨小平, 张中夏, 王良, 等. 基于Word2Vec的情感词典自动构建与优化[J]. 计算机科学, 2017, 44(1): 42-47. |
| [12] | 何炎祥, 孙松涛, 牛菲菲, 等. 用于微博情感分析的一种情感语义增强的深度学习模型[J]. 计算机学报, 2017, 40(4): 773-790. |
