Individual share guba popularity analysis method

Abstract

The invention discloses an individual share guba popularity analysis method, and the method comprises the steps: crawling a financial website and an individual stock bar to obtain corresponding data;drawing up a heat index, and establishing a BOLL band related to a popularity sequence, wherein the BOLL band relates to three lines: a middle track line, an upper track line and a lower track line, the popularity is in a shadow band formed by the upper track line and the lower track line under the condition of normal fluctuation, and a popularity point jumping out of the upper track line or the lower track line is a popularity abnormal point; based on the popularity sequence, finding out popularity change points for a period of time, and fitting the popularity sequence between the two changepoints to obtain a trend chart. According to the invention, the popularity of the individual stock bar is analyzed; the popularity index can be referred to, the attention degree of the public to the specific individual share can be reflected; meanwhile, the moment when the popularity is too high or too low can be monitored, topics or hotspots causing the high popularity can be explored, recommendation bases are provided for individual share recommendation, popular individual share and other characteristic services, and better services are provided for daily decision making of managers or investors.

Description

technical field [0001] The invention relates to a method for analyzing the influence of social media on the securities market, in particular to a method for analyzing the popularity of individual stocks and stock bars. Background technique [0002] The impact of social media on stock market fluctuations is increasing. Investors can obtain real-time information about the securities market through social media, exchange views and feelings on the securities market and individual stocks with others, and participate in various discussions and exchanges in the community . At the same time, information from different channels spreads rapidly in the community through the functions of social media to share, aggregate and amplify information, providing rich decision-making reference information for investors' investment decision-making behaviors. An in-depth analysis of the interaction between the media and the securities market, and a summary of the predictive effect of social media...

AI Technical Summary

Problems solved by technology

[0004] 1. Loud noise: There are many promotional links in advertisements. Generally, the search results of advertisements are ranked at the top; semantic errors, search engines mainly obtain search results based on keywords, not at the semantic level. When there is ambiguity, there are many inaccurate results

[0005] 2. High degree of repetition: For hot news information, major websites will report; in many cases, the title and content are exactly the same, but search engines will not help to remove duplication

[0006] 3. Lack of key indicators: The results of search engines generally only show that the article contains keywords searched by users (here is a stock), but does not indicate how much the stock is related to the article, emotional information (good or bad), investment Investors also need to spend a lot of time and energy to read and analyze before making investment decisions

[0007] 4. No time track: Search engines do not have a time dimension. For stocks that investors care about, they can only obtain current articles and cannot check historical popularity, which is not conducive to investors' decision-making choices

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