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CN-121980033-A - Emotion analysis method and device, storage medium and electronic equipment

CN121980033ACN 121980033 ACN121980033 ACN 121980033ACN-121980033-A

Abstract

The application discloses a mood analysis method, a device, a storage medium and electronic equipment, and relates to the technical field of data processing, wherein the method comprises the steps of obtaining multidimensional text characteristic information of target financial text data; according to the multi-dimensional text characteristic information, identifying a data type corresponding to target financial text data, carrying out emotion analysis on the target financial text data through a plurality of language identification agents and a plurality of financial information agents under the condition that the data type is a complex data type, and carrying out fusion analysis on emotion information obtained by the analysis of the plurality of language identification agents and the plurality of financial information agents to generate target emotion information corresponding to the target financial text data. According to the application, through carrying out fusion analysis on the emotion information obtained by analyzing the plurality of language identification agents and the plurality of financial information agents, the target emotion information corresponding to the target financial text data is generated, so that the targeted processing of different types of data can be realized, and the accuracy of emotion analysis is improved.

Inventors

  • XU GUANGYU

Assignees

  • 北京中科金得助智能科技有限公司

Dates

Publication Date
20260505
Application Date
20251230

Claims (10)

  1. 1. A method of emotion analysis, comprising: acquiring multidimensional text feature information of target financial text data; Identifying a data type corresponding to the target financial text data according to the multi-dimensional text characteristic information; carrying out emotion analysis on the target financial text data through a plurality of language identification agents and a plurality of financial information agents under the condition that the data type is a complex data type; And carrying out fusion analysis on emotion information obtained by analyzing the plurality of language identification agents and the plurality of financial information agents to generate target emotion information corresponding to the target financial text data.
  2. 2. The method of claim 1, wherein the emotion analysis of the target financial text data by a plurality of language identification agents and a plurality of financial information agents comprises: respectively inputting the target financial text data into the plurality of language identification agents; Identifying multi-dimensional language features of the target financial text data in the plurality of language identification agents; And carrying out emotion analysis on the target financial text data according to the multidimensional language features to generate a plurality of pieces of first emotion information corresponding to the target financial text data.
  3. 3. The method of claim 2, wherein the emotion analysis of the target financial text data by a plurality of language identification agents and a plurality of financial information agents comprises: respectively inputting the target financial text data into the plurality of financial information identification agents; Identifying, in the financial information identifying agent, first change information of the target financial text data within a first time range and second change information within a second time range, wherein the second time range is greater than the first time range; and carrying out emotion analysis on the target financial text data according to the first change information and the second change information, and generating second emotion information and third emotion information corresponding to the target financial text data.
  4. 4. The method of claim 3, wherein the performing fusion analysis on emotion information obtained by analyzing the plurality of language identification agents and the plurality of financial information agents to generate target emotion information corresponding to the target financial text data includes: Inputting the target financial text data, the plurality of first emotion information, the second emotion information and the third emotion information into a fusion inference agent; carrying out fusion analysis on the emotion information of the target financial text data according to the plurality of first emotion information, the second emotion information and the third emotion information in the fusion reasoning intelligent agent; and generating target emotion information corresponding to the target financial text data.
  5. 5. The method of claim 1, wherein after the identifying the data type corresponding to the target financial text data from the multi-dimensional text feature information, the method further comprises: inputting the target financial text data into the fusion inference agent under the condition that the data type is a simple data type; and carrying out emotion analysis on the target financial text data in the fusion reasoning intelligent agent to obtain target emotion information corresponding to the target financial text data.
  6. 6. The method of claim 1, wherein the identifying the data type corresponding to the target financial text data based on the multi-dimensional text feature information comprises: Performing feature type analysis on the multi-dimensional text feature information; Under the condition that the preset complex type features exist in the multi-dimensional text feature information, the data type is a complex data type; and under the condition that the preset complex type features do not exist in the multi-dimensional text feature information, the data type is a simple data type.
  7. 7. An emotion analysis device, comprising: the acquisition module is configured to acquire multi-dimensional text characteristic information of the target financial text data; the identification module is configured to identify the data type corresponding to the target financial text data according to the multi-dimensional text characteristic information; An analysis module configured to perform emotion analysis on the target financial text data through a plurality of language identification agents and a plurality of financial information agents in a case where the data type is a complex data type; And the generation module is configured to perform fusion analysis on emotion information obtained by analysis of the plurality of language identification agents and the plurality of financial information agents and generate target emotion information corresponding to the target financial text data.
  8. 8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of any one of claims 1 to 6.
  9. 9. An electronic device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the method of any one of claims 1 to 6 when executing the computer program.
  10. 10. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

Description

Emotion analysis method and device, storage medium and electronic equipment Technical Field The present application relates to the field of data processing technologies, and in particular, to a method and apparatus for emotion analysis, a storage medium, and an electronic device. Background The financial emotion analysis is to judge emotion polarities of related texts in the financial field, and the result of the financial emotion analysis can provide references for decisions of financial market participants, market public opinion monitoring and the like. At present, the existing financial emotion analysis mainly comprises the following steps of learning financial text data by using a general language model, analyzing the financial emotion after the general language model is adapted to the expression and scene in the financial field, and directly designing a question or a guiding speech operation for the language model to complete emotion analysis. However, emotion analysis cannot be performed on financial text data with complicated semantics using this method, resulting in low accuracy of emotion analysis. Disclosure of Invention In view of the above, the present application provides a method, an apparatus, a storage medium and an electronic device for emotion analysis, which are mainly aimed at improving the technical problem that the accuracy of emotion analysis is low because the prior art cannot perform emotion analysis on financial text data with complicated semantics. In a first aspect, the present application provides a mood analysis method comprising: acquiring multidimensional text feature information of target financial text data; Identifying a data type corresponding to the target financial text data according to the multi-dimensional text characteristic information; carrying out emotion analysis on the target financial text data through a plurality of language identification agents and a plurality of financial information agents under the condition that the data type is a complex data type; And carrying out fusion analysis on emotion information obtained by analyzing the plurality of language identification agents and the plurality of financial information agents to generate target emotion information corresponding to the target financial text data. Optionally, the emotion analysis of the target financial text data by a plurality of language identification agents and a plurality of financial information agents includes: respectively inputting the target financial text data into the plurality of language identification agents; Identifying multi-dimensional language features of the target financial text data in the plurality of language identification agents; And carrying out emotion analysis on the target financial text data according to the multidimensional language features to generate a plurality of pieces of first emotion information corresponding to the target financial text data. Optionally, the emotion analysis of the target financial text data by a plurality of language identification agents and a plurality of financial information agents includes: respectively inputting the target financial text data into the plurality of financial information identification agents; Identifying, in the financial information identifying agent, first change information of the target financial text data within a first time range and second change information within a second time range, wherein the second time range is greater than the first time range; and carrying out emotion analysis on the target financial text data according to the first change information and the second change information, and generating second emotion information and third emotion information corresponding to the target financial text data. Optionally, the performing fusion analysis on the emotion information obtained by analyzing the plurality of language identification agents and the plurality of financial information agents to generate target emotion information corresponding to the target financial text data includes: Inputting the target financial text data, the plurality of first emotion information, the second emotion information and the third emotion information into a fusion inference agent; carrying out fusion analysis on the emotion information of the target financial text data according to the plurality of first emotion information, the second emotion information and the third emotion information in the fusion reasoning intelligent agent; and generating target emotion information corresponding to the target financial text data. Optionally, after the identifying the data type corresponding to the target financial text data according to the multi-dimensional text feature information, the method further includes: inputting the target financial text data into the fusion inference agent under the condition that the data type is a simple data type; and carrying out emotion analysis on the target financial text data in the fusio