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An emotion dictionary construction method capable of being automatically updated and used for financial text analysis

A construction method and automatic update technology, applied in unstructured text data retrieval, semantic tool creation, electronic digital data processing, etc., can solve the problems of immature Chinese language analysis tools, poor quality of Chinese sentiment dictionary, lack of accuracy, etc.

Active Publication Date: 2019-06-28
BEIJING NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

However, due to the inherent differences between Chinese and English, the immaturity of Chinese language analysis tools, and the blunt copying of English analysis models, the quality of Chinese sentiment dictionaries is poor.
In addition, with the rapid development of the financial field, a large number of new words and hot words are constantly emerging, which makes the text analysis results based on traditional sentiment dictionaries lack of accuracy

Method used

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  • An emotion dictionary construction method capable of being automatically updated and used for financial text analysis
  • An emotion dictionary construction method capable of being automatically updated and used for financial text analysis
  • An emotion dictionary construction method capable of being automatically updated and used for financial text analysis

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Embodiment 1

[0033] Step 1. Build a basic emotional dictionary. Integrating existing sentiment dictionaries, the present invention uses the currently widely recognized Hownet sentiment dictionary and the Simplified Chinese sentiment polarity dictionary (NTUSD) of National Taiwan University. The Chinese sentiment dictionary included in Hownet Sentiment Dictionary includes: positive sentiment words, positive evaluation words, negative sentiment words, negative evaluation words, level-level words and advocacy words. The Simplified Chinese Affective Polarity Dictionary of National Taiwan University includes: ntusd-negative and ntusd-positive two emotional dictionaries. The specific integration method is to merge the positive evaluation words, positive emotion words and ntusd positive dictionary in Hownet to get the positive emotion dictionary, and merge the negative evaluation words, negative emotion words and ntusd in Hownet. The negative emotion dictionary is merged to get the negative emoti...

Embodiment 2

[0053] The emotion dictionary is constructed using the same process as in Example 1, except that α=0.6, β=0.4, and finally the emotion dictionary D is obtained. update-2 .

Embodiment 3

[0055] Step 1. Build a basic emotional dictionary. Integrating existing sentiment dictionaries, the present invention adopts the currently widely recognized Hownet Sentiment Dictionary and the Simplified Chinese Simplified Chinese Affective Polarity Dictionary (NTUSD) of Taiwan University. The Chinese sentiment dictionary included in Hownet Sentiment Dictionary includes: positive sentiment words, positive evaluation words, negative sentiment words, negative evaluation words, degree-level words and advocacy words. The Simplified Chinese Affective Polarity Dictionary of National Taiwan University includes: ntusd-negative and ntusd-positive two emotional dictionaries. The specific integration method is to merge the positive evaluation words, positive emotion words and ntusd positive dictionary in Hownet to get the positive emotion dictionary, and merge the negative evaluation words, negative emotion words and ntusd in Hownet. The negative emotion dictionary is merged to get the n...

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Abstract

The invention discloses an emotion dictionary construction method capable of being automatically updated and used for financial text analysis. The method comprises the following steps of: forming a basic dictionary Dinial by utilizing an existing sentiment dictionary in a knowledge base; the basic emotion dictionary is expanded by means of machine adding and manual adding; obtaining an extended emotion dictionary Dextend; improving the new word extraction accuracy by calculating the prefix and suffix information entropy, then conducting probability calculation on new words extracted from a corpus through a naive Bayes classifier and the emotional tendency probability, and adding the emotional words which meet the condition and have positive or negative emotions into an emotional dictionary by setting a threshold value. Compared with the prior art, the method has the advantages that (1) new words are extracted more accurately, and noise and subsequent calculation amount are reduced; (2) the emotion analysis calculation amount is small, and a more accurate emotion analysis result can be obtained through parameter optimization; and (3) the sentiment dictionary can be continuously updated as required, so that the accuracy of the financial text sentiment analysis method based on the sentiment dictionary is improved.

Description

Technical field [0001] The invention belongs to the technical field of text sentiment analysis and opinion mining, and specifically is an sentiment dictionary construction method for financial text analysis. Background technique [0002] Changes in investor sentiment have a huge impact on their investment decisions. The investment sentiment of most small and medium investors is easily influenced by public opinion and the remarks of other investors. Therefore, it is particularly important to quantitatively calculate and analyze the sentiment value of investors on individual stocks and various sectors. It can provide a reference for investors to make investment decisions and can also be used as a stock selection factor construction model for quantitative trading. Therefore, analyzing investor sentiment has become an increasingly important research area. [0003] By analyzing various commentary texts on financial markets on the Internet, investors can effectively obtain their views ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/36G06F17/27
Inventor 孙运传王欣宇沈岩方梦婷别荣芳崔学刚
Owner BEIJING NORMAL UNIVERSITY
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