Deep Learning Based Sentiment Analysis: A Survey

Authors

DOI:

https://doi.org/10.26438/ijcse/v12i6.5563

Keywords:

Text analysis, Natural language processing, sentiment analysis, prediction, machine learning

Abstract

Sentiment analysis, a pivotal area within natural language processing, has witnessed significant advancements with the advent of deep learning methodologies. This survey provides a comprehensive overview of the state-of-the-art in sentiment analysis, focusing specifically on the application of deep learning techniques. The aim is to present a thorough exploration of the existing literature, methodologies, and challenges associated with leveraging deep neural networks for sentiment analysis tasks.

References

[1] Liu B. Sentiment analysis: mining opinions, sentiments, and emotions. The Cambridge University Press, 2015.

[2] Liu B. Sentiment analysis and opinion mining (introduction and survey), Morgan & Claypool, May 2012.

[3] Pang B and Lee L. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2): pp.1–135, 2008.

[4] Goodfellow I, Bengio Y, Courville A. Deep learning. The MIT Press. 2016.

[5] Nirmala vargesh babu,E grace Mary ganga. Sentiment Analysis in Social Media Data for Depression Detection Using Artificial Intelligence: A Review Springer, 2022.

[6] Avishek Garain, Sainik Kumar Mahata. Sentiment Analysis at SEPLN (TASS)-2019: Sentiment Analysis at Tweet level using Deep Learning, 2019.

[7] Graph Convolutional Networks for Text Classification Liang Yao, Chengsheng Mao, Yuan Luo*. The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI-19, 2019.

[8] Abdalraouf Hassan and Ausif Mamhmood, “Convolutional recurrent deep learning model for sentence classification,” in IEEE Access, Vol.6, pp.13949-13957, 2018.

[9] Z. Jianqiang, G. Xiaolin and Z. Xuejun, "Deep convolution neural networks for twitter sentiment analysis," in IEEE Access, Vol.6, pp.23253-23260, 2018.

[10] Z. Z. Wint, Y. Manabe and M. Aritsugi, "Deep learning based sentiment classification in social network services datasets," 2018 IEEE International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD), Yonago, pp.91-96, 2018.

[11] K. Baktha and B. K. Tripathy, "Investigation of recurrent neural networks in the field of sentiment analysis," 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, pp.2047-2050, 2017.

[12] Liu P, Qiu X, Huang X (2016) Recurrent neural network for text classification with multi-task learning. arXiv preprint arXiv: 16050 5101, 2016.

[13] Zhou X, Wan X, Xiao J. Attention-based LSTM network for cross-lingual sentiment classification. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.

[14] Tai K.S, Socher R, Manning C. D. Improved semantic representations from tree-structured long short-term memory networks. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2015), 2015.

[15] Cho K, Bahdanau D, Bougares F, Schwenk H and Bengio Y. Learning phrase representations using RNN encoder-decoder for statistical machine translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), 2014.

[16] Zhou, Chunting & Sun, Chonglin & Liu, Zhiyuan & Lau, Francis. “A C-LSTM neural network for text classification”, 2015.

[17] J. Panthati, J. Bhaskar, T. K. Ranga and M. R. Challa, "Sentiment analysis of product reviews using deep learning," 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore 2018, pp.2408-2414, 2018.

[18] Adyan Marendra Ramadhani and Hong Soon Goo, “Twitter sentiment analysis using deep learning methods,” 7th International Annual Engineering Seminar (InAES), Indonesia, 2017.

[19] Kim, Y., Convolutional neural networks for sentence classification, 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, pp.1746–1751, 2014.

Downloads

Published

2024-06-30
CITATION
DOI: 10.26438/ijcse/v12i6.5563
Published: 2024-06-30

How to Cite

[1]
L. Singh, C. Agrawal, and P. Meena, “Deep Learning Based Sentiment Analysis: A Survey”, Int. J. Comp. Sci. Eng., vol. 12, no. 6, pp. 55–63, Jun. 2024.

Issue

Section

Survey Article