Financial text sentiment analysis method

A sentiment analysis and text technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as time-consuming and labor-intensive construction of emotional word dictionaries, influence of model noise, and impact on the quality of training samples

Active Publication Date: 2015-12-09
TIANYUN RONGCHUANG DATA TECH BEIJING CO LTD
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Problems solved by technology

The established classification model has a lot to do with the specific field, and the model built for one field is usually not suitable for another field, and the construction of the emotional word dictionary is time-consumin...

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  • Financial text sentiment analysis method

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Embodiment Construction

[0074] The "financial sentiment analysis method" of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0075] The present invention provides a kind of financial emotion analysis method, at first construct emotion dictionary and user dictionary with software tool, to financial news or message text sentence by sentence segmentation, then calculate the article emotion value of multiplication emotion model and the article emotion value of addition emotion model, Finally, the two models are fused by weighted combination. as attached figure 1 As shown, the specific steps are as follows:

[0076] 1. Build a dictionary. The dictionaries that need to be constructed include the sentiment dictionary of positive sentiment words (including financial sentiment words), the sentiment dictionary of negative sentiment tendencies words (including financial sentiment words), the sentiment dictionary of uncertain words ...

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Abstract

The invention relates to a financial text sentiment analysis method, comprising the following operational steps of: firstly, constructing a financial sentiment dictionary; secondly, performing sentence segmentation on a text, performing word segmentation, and generating a word segmentation sequence vector comprising a word text, a word property and a word sentiment value; thirdly, correcting the influence of a negative word, a degree word, a single concept word, a transitional word, a standard word and the like on the sentiment value; fourthly, calculating a fused financial text sentiment value by using weighted combination of a multiplication sentiment model for calculation of a sentiment generation function and an addition sentiment model for words in articles; and fifthly, compatibly expressing sentiment values [0,2] and [-1,1]. According to the method, for different sentiment environments, an input layer is applied as a word, a hidden layer is applied as a sentence sentiment layer expressed by the sentiment generation function, and an output layer is applied as a neural network of a nerve cell to calculate financial sentiment.

Description

technical field [0001] The invention relates to the fields of natural language processing and artificial intelligence, in particular to a financial text sentiment analysis method. Background technique [0002] With the popularity of the Internet, people's lives have also undergone great changes. The Internet has gradually become the carrier of various information in society. Especially with the continuous development of China's economy, financial products such as stocks and national bonds have gradually become hot topics for people to discuss. More and more people obtain financial, financial, and other economic information through the Internet. News and related information. Web text has also become an important source for us to obtain information, express opinions and exchange emotions. More and more people like to exchange their opinions on the Internet, so there are a lot of tendentious text information on the Internet. [0003] The general sentiment analysis is to iden...

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Application Information

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IPC IPC(8): G06F17/27
Inventor 雷涛邵明东吕慧
Owner TIANYUN RONGCHUANG DATA TECH BEIJING CO LTD
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