News data-based individual share emotion convergence method

A technology of news data and news, applied in the direction of network data retrieval, network data indexing, electronic digital data processing, etc., can solve the problems of unfavorable individual investor decision-making, loss of useful information, etc., and achieve the effect of short-term understanding and good investment judgment

Inactive Publication Date: 2017-11-17
SUN YAT SEN UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

Such an abstract value greatly loses the useful information in the news. If investors want to understand and analyze individual stock news in detail, they must read the full ...

Method used

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  • News data-based individual share emotion convergence method
  • News data-based individual share emotion convergence method
  • News data-based individual share emotion convergence method

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Experimental program
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Embodiment Construction

[0047] The present invention will be further described below in conjunction with specific embodiment:

[0048] See attached figure 1 As shown, a kind of news data-based individual stock sentiment aggregation method described in this embodiment includes the following steps:

[0049] S1. Use crawler tools to crawl the title, time, source, content, number of reprints, and number of comments of relevant news information from major news websites to form news documents d i ;

[0050] S2. Press document to be formed d i stored in a document storage database;

[0051] S3. Calculate the popularity of each article and remove duplicate documents;

[0052] Calculated as follows:

[0053] newsHeat=∑forward i +∑comment i ,

[0054] Among them, ∑forward i Represents the forwarding quantity of news i, ∑comment i Represents the number of comments on news i.

[0055] S4. The news document d in the database is documented as a unit i content in i Items are preprocessed to form a text...

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Abstract

The invention relates to a news data-based individual share emotion convergence method. The method comprises the following steps of: 1, crawling news information to form news documents and storing the news documents into a document storage database; 2, calculating the heat of each document and removing the repeated documents; 3, preprocessing content items in the news documents to form text sets; 4, carrying out comprehensive emotion analysis and theme analysis on each text set to form a two-tuple set, and carrying out text theme clustering and grouping; 5, integrating all the related financial reports to form an individual share-based triple set; 6, converging above results by taking individual shares as center; and 7, selecting a visible system to display the results to users. According to the method, correct and high-readability simplified theme emotion information can be provided for investors of financial markets, the investors can be helped to understand and better carry out investment judgement through shorter time, and important prediction model auxiliary information can be provided for quantifying the fund companies.

Description

technical field [0001] The invention relates to the technical field of network data analysis, in particular to a news data-based individual stock sentiment aggregation method. Background technique [0002] The securities market is known as the "barometer" of a country's economy. The economic operation is cyclical, and the securities market can take the lead in reflecting the economic situation. For a long time, many economists and stock market researchers have devoted themselves to building effective stock market analysis and forecasting models and formed systematic analysis methods. Classic securities investment analysis methods include fundamental analysis and technical analysis. The basic analysis method is divided into three layers from top to bottom, specifically including macroeconomic analysis, industry analysis and enterprise value analysis; technical analysis method is a method of analyzing changes in the stock market, usually using a combination of capital pricing...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/34G06F16/951
Inventor 郑子彬翁灵玲周育人
Owner SUN YAT SEN UNIV
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