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Sentiment dictionary-based sentiment analysis method for fine-grained entities in financial news

A technology of emotion dictionary and emotion analysis, applied in semantic analysis, special data processing applications, instruments, etc., can solve the problem of not considering the attribution of emotion word entities, unable to analyze and express the emotion polarity of each entity, etc.

Pending Publication Date: 2020-04-17
新华智云科技有限公司
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the sentiment analysis method of the existing sentiment lexicon does not consider the entity attribution of sentiment words. Especially for listed companies, when there are multiple entities in the news and the sentiment orientation of the entities is inconsistent, it is impossible to determine the sentiment polarity of each entity. have accurate analysis and presentation

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  • Sentiment dictionary-based sentiment analysis method for fine-grained entities in financial news
  • Sentiment dictionary-based sentiment analysis method for fine-grained entities in financial news

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Embodiment Construction

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0024] see figure 1 with figure 2 As shown, the present invention provides a kind of technical scheme:

[0025] The present invention provides the emotion analysis method of fine-grained entity in the financial news based on emotion dictionary, and its method comprises the following steps:

[0026] S1. Analyze a large amount of financial news and build a financial-specific emotional dictionary, negative words, and degree adverbs;

[0027] S2. For the finan...

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Abstract

The invention relates to the technical field of sentiment dictionary analysis, in particular to a sentiment dictionary-based sentiment analysis method for fine-grained entities in financial news. Themethod comprises the following steps: analyzing a large amount of financial news; obtaining all listed company entity sets of the news to be analyzed on the basis of existing data service-entity identification and extraction of the company; filtering to obtain a listed company sentiment sentence set only containing sentiment words from the listed company sentence set obtained in S2; traversing each word of the sentiment sentence subjected to word segmentation filtered in the step S3, and judging whether the word is a sentiment word or not; performing weighted summation on the emotion scores ofall emotion sentences obtained by each listed company in the step S4; and performing polarity division on the emotion scores. According to the sentiment dictionary-based sentiment analysis method forthe fine-grained entities in the financial news, sentiment analysis and calculation are performed on each listed company in the news by adopting a sentiment dictionary method, sentiment analysis is performed on each listed company involved in the financial news, and the sentiment polarity of each listed company of each article can be obtained.

Description

technical field [0001] The invention relates to the technical field of sentiment dictionary analysis, in particular to a sentiment analysis method for fine-grained entities in financial news based on sentiment dictionary. Background technique [0002] The existing sentiment analysis method based on the sentiment lexicon mainly solves the overall sentiment polarity of the news text. Its core idea is to find the sentiment words, negative words and degree adverbs in the text by segmenting the news text, and then judge each sentiment word Whether there are negative words and adverbs of degree before it, divide the negative words and adverbs of degree before it into a group, and finally add up the scores of all groups, and those greater than 0 are classified as positive, and those less than 0 are classified as negative. However, the sentiment analysis method of the existing sentiment lexicon does not consider the entity attribution of sentiment words. Especially for listed compan...

Claims

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Application Information

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IPC IPC(8): G06F40/289G06F40/211G06F40/30G06F16/36
CPCG06F16/367
Inventor 张明
Owner 新华智云科技有限公司
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