Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis

Haiyun Peng; Soujanya Poria; Yang Li; Erik Cambria

doi:10.1007/978-3-031-24340-0_12

Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis

Haiyun Peng, Soujanya Poria, Yang Li, Erik Cambria

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Hence, we learn phonetic features of Chinese characters and fuse them with their textual and visual features in order to mimic the way humans read and understand Chinese text. Experimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations.

Original language	English
Title of host publication	Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers
Editors	Alexander Gelbukh
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	151-165
Number of pages	15
ISBN (Print)	9783031243394
DOIs	https://doi.org/10.1007/978-3-031-24340-0_12
State	Published - 2023
Externally published	Yes
Event	20th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2019 - La Rochelle, France Duration: 7 Apr 2019 → 13 Apr 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13452 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2019
Country/Territory	France
City	La Rochelle
Period	7/04/19 → 13/04/19

Keywords

Character representation
Phonetic features
Sentiment analysis

Access to Document

10.1007/978-3-031-24340-0_12

Cite this

Peng, H., Poria, S., Li, Y., & Cambria, E. (2023). Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis. In A. Gelbukh (Ed.), Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers (pp. 151-165). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13452 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-24340-0_12

Peng, Haiyun ; Poria, Soujanya ; Li, Yang et al. / Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis. Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers. editor / Alexander Gelbukh. Springer Science and Business Media Deutschland GmbH, 2023. pp. 151-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Hence, we learn phonetic features of Chinese characters and fuse them with their textual and visual features in order to mimic the way humans read and understand Chinese text. Experimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations.",

keywords = "Character representation, Phonetic features, Sentiment analysis",

author = "Haiyun Peng and Soujanya Poria and Yang Li and Erik Cambria",

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doi = "10.1007/978-3-031-24340-0_12",

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isbn = "9783031243394",

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Peng, H, Poria, S, Li, Y & Cambria, E 2023, Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis. in A Gelbukh (ed.), Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13452 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 151-165, 20th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2019, La Rochelle, France, 7/04/19. https://doi.org/10.1007/978-3-031-24340-0_12

Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis. / Peng, Haiyun; Poria, Soujanya; Li, Yang et al.
Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers. ed. / Alexander Gelbukh. Springer Science and Business Media Deutschland GmbH, 2023. p. 151-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13452 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Hence, we learn phonetic features of Chinese characters and fuse them with their textual and visual features in order to mimic the way humans read and understand Chinese text. Experimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations.

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Peng H, Poria S, Li Y, Cambria E. Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis. In Gelbukh A, editor, Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2023. p. 151-165. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-24340-0_12