CN112988973A - Talent emotional tendency detection method based on emotional word matching - Google Patents
Talent emotional tendency detection method based on emotional word matching Download PDFInfo
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Abstract
The invention relates to a talent emotional tendency detection method based on emotional word matching, which specifically comprises the following steps: s1, acquiring identity information of the talent to be evaluated, and determining the user name of the talent to be evaluated on the social network platform according to the identity information; s2, collecting social information of talents to be evaluated on a social network platform according to the user name, extracting emotion keywords from the social information, and classifying the extracted emotion keywords; and S3, matching the classified emotion keywords with the emotion word libraries of corresponding categories, and determining the talent emotion tendencies of the talents to be evaluated according to matching results. Compared with the prior art, the method has the advantages of expanding the range of the basic word source during emotional word analysis, improving the accuracy and stability of the talent emotional tendency analysis result and the like.
Description
Technical Field
The invention relates to the field of talent evaluation, in particular to a talent emotional tendency detection method based on emotional word matching.
Background
The emotional tendency is a tendency that a subject subjectively has internal happiness and dislike and internal evaluation on a certain object, and has degree and object; the emotion is a part of the attitude, has coordination consistency with the inward feeling and the intention in the attitude, and is a physiologically complex and stable physiological evaluation and experience of the attitude. The emotion includes the moral feeling and the value feeling.
At present, the identification of word emotion tendentiousness is mature, useful tendency information and knowledge obtained aiming at text content become research hotspots of natural language processing, methods and technologies for emotion word identification and emotion word polarity judgment are formed, for example, the emotion word tendency obtained through numerical calculation, and the method for acquiring the emotion word tendency by utilizing the constructed seed emotion word tendency and the emotion word tendency calculated based on word connection property; the method also comprises an emotion tendency analysis method based on an emotion dictionary method, wherein an emotion concept dictionary is provided, the influence degree of different types of emotion words on text emotion is determined by calculating vocabulary similarity, and an emotion score strategy is designed, so that the emotion tendency of the text is accurately analyzed.
However, in the current method, only the matching of emotional words and emotional tendencies is studied, the sources and associated sources of the emotional words are not considered, and emotional tendency evaluation and judgment for talent evaluation are not available.
Disclosure of Invention
The invention aims to provide a talent emotional tendency detection method based on emotional word matching to overcome the defect that the analysis of the source and the associated source of the emotional words is lacked in the emotional word analysis in the prior art.
The purpose of the invention can be realized by the following technical scheme:
a talent emotional tendency detection method based on emotional word matching specifically comprises the following steps:
s1, acquiring identity information of the talent to be evaluated, and determining the user name of the talent to be evaluated on the social network platform according to the identity information;
s2, collecting social information of talents to be evaluated on a social network platform according to the user name, extracting emotion keywords from the social information, and classifying the extracted emotion keywords;
and S3, matching the classified emotion keywords with the emotion word libraries of corresponding categories, and determining the talent emotion tendencies of the talents to be evaluated according to matching results.
The identity information of the talents to be evaluated comprises an arbitrary mechanism, identity characteristics and friend circle information.
The number of the social network platforms is 1 or more than 1.
Further, the user names of talents to be evaluated in the 2 or more than 2 social network platforms are the same.
The step S1 further includes verifying the determined user name.
The social information in step S2 includes text content of an operation record of the talent to be evaluated in the social network platform, and is obtained by searching through a big data technology.
Further, the text content of the operation record existing in the social network platform specifically includes the text content of the talent to be evaluated, which is published, forwarded and approved.
In the step S2, the extracted emotion keywords are classified by a semantic analysis algorithm.
The emotion lexicon in the step S3 is based on a public opinion expert analysis system.
The process of determining the talent emotional tendency of the talent to be evaluated according to the matching result in the step S3 is specifically to obtain an emotional tendency radar chart according to the matching result, and determine the talent emotional tendency of the talent to be evaluated according to the emotional tendency radar chart.
Compared with the prior art, the invention has the following beneficial effects:
according to the method, the user name of the talent to be evaluated in the social network platform is determined, the text content of the talent to be evaluated, which is published, forwarded and liked, in the social network platform is collected, the emotion keywords are extracted and then matched with the emotion word bank of the corresponding category, the emotional tendency of the talent to be evaluated is determined through the emotional tendency radar map, the basic word source range during emotional word analysis is expanded, the use frequency of the social network platform is high, and the accuracy and the stability of the emotional tendency analysis result of the talent can be effectively improved based on the social information of the talent to be evaluated in the social network platform.
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FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Examples
As shown in FIG. 1, a talent emotional tendency detection method based on emotional word matching specifically includes the following steps:
s1, acquiring identity information of the talent to be evaluated, and determining the user name of the talent to be evaluated on the social network platform according to the identity information;
s2, collecting social information of talents to be evaluated on a social network platform according to the user name, extracting emotion keywords from the social information, and classifying the extracted emotion keywords;
and S3, matching the classified emotion keywords with the emotion word libraries of corresponding categories, and determining the talent emotion tendencies of the talents to be evaluated according to matching results.
The identity information of the talents to be evaluated comprises an arbitrary mechanism, identity characteristics and friend circle information.
The number of social network platforms is 1 or more than 1.
The user names of talents to be evaluated in 2 or more than 2 social network platforms are the same.
Step S1 further includes verifying the determined user name, and in this embodiment, the accuracy of the user name is verified according to the statistical result by counting the time and the place of the content of the talent to be evaluated, which is disclosed on the social network platform.
The social information in step S2 includes text content of an operation record of the talent to be evaluated in the social network platform, and is obtained by searching through a big data technology.
The text content of the operation record in the social network platform specifically comprises the text content of the talent to be evaluated, which is published, forwarded and favored.
In step S2, the extracted emotion keywords are classified by a semantic analysis algorithm.
The emotion vocabulary library in step S3 is based on the public opinion expert analysis system.
The process of determining the talent emotional tendency of the talent to be evaluated according to the matching result in step S3 is specifically to obtain an emotional tendency radar chart according to the matching result, and determine the talent emotional tendency of the talent to be evaluated according to the emotional tendency radar chart.
In addition, it should be noted that the specific embodiments described in the present specification may have different names, and the above descriptions in the present specification are only illustrations of the structures of the present invention. All equivalent or simple changes in the structure, characteristics and principles of the invention are included in the protection scope of the invention. Various modifications or additions may be made to the described embodiments or methods may be similarly employed by those skilled in the art without departing from the scope of the invention as defined in the appending claims.
Claims (10)
1. A talent emotional tendency detection method based on emotional word matching is characterized by comprising the following steps:
s1, acquiring identity information of the talent to be evaluated, and determining the user name of the talent to be evaluated on the social network platform according to the identity information;
s2, collecting social information of talents to be evaluated on a social network platform according to the user name, extracting emotion keywords from the social information, and classifying the extracted emotion keywords;
and S3, matching the classified emotion keywords with the emotion word libraries of corresponding categories, and determining the talent emotion tendencies of the talents to be evaluated according to matching results.
2. The talent emotional tendency detection method based on emotional word matching as claimed in claim 1, wherein the identity information of talents to be evaluated comprises any institution, identity characteristics and circle of friends information.
3. The talent emotional tendency detection method based on emotional word matching as claimed in claim 1, wherein the number of the social network platforms is 1 or more than 1.
4. The talent emotional tendency detection method based on emotional word matching as claimed in claim 3, wherein the user names of talents to be evaluated in the 2 or more than 2 social network platforms are the same.
5. The method for detecting emotional tendencies of talents based on emotion word matching as claimed in claim 1, wherein said step S1 further comprises verifying said determined user name.
6. The method for detecting emotional tendency of talents based on emotional word matching as claimed in claim 1, wherein the social information in step S2 includes text content of operational records of talents to be evaluated in the social networking platform.
7. The method as claimed in claim 6, wherein the text content of the operation records in the social network platform specifically includes text content of public publishing, forwarding and praise of the talent to be evaluated.
8. The method for detecting talent emotional tendency based on emotional word matching as claimed in claim 1, wherein the extracted emotional keywords are classified by semantic analysis algorithm in step S2.
9. The method as claimed in claim 1, wherein the emotion vocabulary library of step S3 is based on a consensus analysis system.
10. The talent emotional tendency detection method based on emotional word matching according to claim 1, wherein the step of determining the emotional tendency of the talent to be evaluated according to the matching result in step S3 is to obtain an emotional tendency radar chart according to the matching result, and determine the emotional tendency of the talent to be evaluated according to the emotional tendency radar chart.
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Citations (6)
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| CN106096664A (en) * | 2016-06-23 | 2016-11-09 | 广州云数信息科技有限公司 | A kind of sentiment analysis method based on social network data |
| CN106294532A (en) * | 2016-05-18 | 2017-01-04 | 广东电网有限责任公司信息中心 | The image appraisal algorithm analyzed based on microblog emotional |
| KR101733911B1 (en) * | 2016-02-12 | 2017-05-24 | 전북대학교산학협력단 | Module for analyzing of subscriber's tendency by uploaded contents to social network |
| CN108549632A (en) * | 2018-04-03 | 2018-09-18 | 重庆邮电大学 | A kind of social network influence power propagation model construction method based on sentiment analysis |
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2021
- 2021-03-25 CN CN202110319695.XA patent/CN112988973A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101408883A (en) * | 2008-11-24 | 2009-04-15 | 电子科技大学 | Method for collecting network public feelings viewpoint |
| KR101733911B1 (en) * | 2016-02-12 | 2017-05-24 | 전북대학교산학협력단 | Module for analyzing of subscriber's tendency by uploaded contents to social network |
| CN106021925A (en) * | 2016-05-18 | 2016-10-12 | 大连理工大学 | Psychological assessment system based on text sentiment analysis |
| CN106294532A (en) * | 2016-05-18 | 2017-01-04 | 广东电网有限责任公司信息中心 | The image appraisal algorithm analyzed based on microblog emotional |
| CN106096664A (en) * | 2016-06-23 | 2016-11-09 | 广州云数信息科技有限公司 | A kind of sentiment analysis method based on social network data |
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Application publication date: 20210618 |