@inproceedings{9c3f566d57184707b2ea49559c3950af,
title = "Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis",
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",
note = "Publisher Copyright: {\textcopyright} 2023, Springer Nature Switzerland AG.; 20th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2019 ; Conference date: 07-04-2019 Through 13-04-2019",
year = "2023",
doi = "10.1007/978-3-031-24340-0\_12",
language = "英语",
isbn = "9783031243394",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "151--165",
editor = "Alexander Gelbukh",
booktitle = "Computational Linguistics and Intelligent Text Processing - 20th International Conference, CICLing 2019, Revised Selected Papers",
}