Learning sentiment-inherent word embedding for word-level and sentence-level sentiment analysis

Proceedings of 2015 International Conference on Asian Language Processing, IALP 2015

Volumn , Issue , 2016, Pages 94-97

  Zhang, Zhihua ^a   Lan, Man ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; DATA MINING; SEMANTICS;

GRAM MODELS; NATURAL LANGUAGE PROCESSING; SEMANTIC INFORMATION; SENTENCE LEVEL; SENTIMENT ANALYSIS; WORD LEVEL; WORD REPRESENTATIONS; WORD VECTORS;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84970027709     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IALP.2015.7451540     Document Type: Conference Paper

References (15)

1. Y. Bengio, R. Ducharme, P. Vincent, and C. Janvin, "A neural probabilistic language model, " T he Journal of Machine Learning Research, vol. 3, pp. 1137-1155, 2003.
2. R. Collobert, "Deep learning for etlicient discriminative parsing, " in International Conference on Artificial Intelligence and Statistics, no. EPFL-CONF-192374, 2011.
3. R. Coli obert, J. Weston, L. Bottou, M. Karlen, K. Kavukcuoglu, and P. Kuksa, "Natural language processing (almost) from scratch, " T he Journal of Machine Learning Research, vol. 12, pp. 2493-2537, 2011.
4. L. Dong, F. Wei, C. Tan, D. Tang, M. Zhou, and K. Xu, "Adaptive recursive neural network for target-dependent twitter sentiment classification, " in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014, pp. 49-54.
5. S.-M. Kim and E. Hovy, "Determining the sentiment of opinions, " in Proceedings of the 20th international conference on Computational Linguistics. Association for Computational Linguistics, 2004, p. 1367.
6. Y. Kim, "Convolutional neural networks for sentence classification, " arXiv preprint arXiv: 1408. 5882, 2014.
7. B. Liu, "Sentiment analysis and opinion mining, " Synthesis Lectures on Human Language Technologies, vol. 5, no. I, pp. 1-167, 2012.
8. A. L. Maas, R. E. Daly, P. T. Pham, D. Huang, A. Y. Ng, and C. Potts, "Learning word vectors for sentiment analysis, " in Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1. Association for Computational Linguistics, 20 II, pp. 142-150.
9. T. Mikolov, K. Chen, G. Corrado, and J. Dean, "Efficient estimation of word representations in vector space, " arXiv preprint arXiv: 1301. 3781, 2013.
10. S. M. Mohammad, S. Kiritchenko, a nd X. Zhu, " NRC-Canada: Building the state-of-the-art in sentiment analysis of tweets, " in Proceedings of the Second Joint Conference on Lexical and Computational Semantics (SEMSTAR'13), 2013.
11. B. Pang, L. Lee, and S. Vaithyanathan, "Thumbs up?: sentiment classification using machine learning techniques, " in Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10. Association for Computational Linguistics, 2002, pp. 79-86.
12. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning representations by back-propagating errors, " Cognitive modeling, vol. 5, 1988.
13. D. Tang, F. Wei, N. Yang, M. Zhou, T. Liu, and B. Qin, "Learning sentiment-specific word embedding for twitter sentiment classification, " in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014, pp. 1555-1565.
14. J. Turian, L. Ratinov, and Y. Bengio, "Word representations: A simple and general method for semi-supervised learning, " in Proceedings of the 48th annual meeting of the association for computational linguistics. Association for Computational Linguistics, 2010, pp. 384-394.
15. J. Zhao, K. Liu, a nd G. Wang, " Adding redundant features for crfs-based sentence sentiment classification, " in Proceedings of the conference on empirical methods in natural language processing. Association for Computational Linguistics, 2008, pp. 117-126.