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Characters-based sentiment identification method for short and informal Chinese text

Characters-based sentiment identification method for short and informal Chinese text PurposeSentiment identification of Chinese text faces many challenges, such as requiring complex preprocessing steps, preparing various word dictionaries carefully and dealing with a lot of informal expressions, which lead to high computational complexity.Design/methodology/approachA method based on Chinese characters instead of words is proposed. This method represents the text into a fixed length vector and introduces the chi-square statistic to measure the categorical sentiment score of a Chinese character. Based on these, the sentiment identification could be accomplished through four main steps.FindingsExperiments on corpus with various themes indicate that the performance of proposed method is a little bit worse than existing Chinese words-based methods on most texts, but with improved performance on short and informal texts. Especially, the computation complexity of the proposed method is far better than words-based methods.Originality/valueThe proposed method exploits the property of Chinese characters being a linguistic unit with semantic information. Contrasting to word-based methods, the computational efficiency of this method is significantly improved at slight loss of accuracy. It is more sententious and cuts off the problems resulted from preparing predefined dictionaries and various data preprocessing. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information Discovery and Delivery Emerald Publishing

Characters-based sentiment identification method for short and informal Chinese text

Lan, Qiujun; Ma, Haojie; Li, Gang
Information Discovery and Delivery , Volume 46 (1): 10 – Feb 19, 2018
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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2398-6247
DOI
10.1108/IDD-05-2017-0047
Publisher site
See Article on Publisher Site

Abstract

PurposeSentiment identification of Chinese text faces many challenges, such as requiring complex preprocessing steps, preparing various word dictionaries carefully and dealing with a lot of informal expressions, which lead to high computational complexity.Design/methodology/approachA method based on Chinese characters instead of words is proposed. This method represents the text into a fixed length vector and introduces the chi-square statistic to measure the categorical sentiment score of a Chinese character. Based on these, the sentiment identification could be accomplished through four main steps.FindingsExperiments on corpus with various themes indicate that the performance of proposed method is a little bit worse than existing Chinese words-based methods on most texts, but with improved performance on short and informal texts. Especially, the computation complexity of the proposed method is far better than words-based methods.Originality/valueThe proposed method exploits the property of Chinese characters being a linguistic unit with semantic information. Contrasting to word-based methods, the computational efficiency of this method is significantly improved at slight loss of accuracy. It is more sententious and cuts off the problems resulted from preparing predefined dictionaries and various data preprocessing.

Journal

Information Discovery and Delivery – Emerald Publishing

Published: Feb 19, 2018

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