CN115907465A - Reputation risk positioning analysis method and system based on risk positioning model - Google Patents
Reputation risk positioning analysis method and system based on risk positioning model Download PDFInfo
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- CN115907465A CN115907465A CN202211401169.9A CN202211401169A CN115907465A CN 115907465 A CN115907465 A CN 115907465A CN 202211401169 A CN202211401169 A CN 202211401169A CN 115907465 A CN115907465 A CN 115907465A
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Abstract
The invention provides a reputation risk positioning analysis method and a reputation risk positioning analysis system based on a risk positioning model, and belongs to the technical field of reputation risk management; wherein the method comprises the following steps: the retrieval frame acquires public opinion studying and judging data, and the public opinion studying and judging data is associated with a specified public opinion main object; analyzing the public opinion research and judgment data to complete the positioning of stakeholders and the positioning of event causal relationship; the data model outputs the investigation result of the public sentiment event based on the association rule of the causal relationship between the stakeholders and the event. The scheme of the invention models the reputation risk positioning, solves the problems of high difficulty and long time of traditional manual examination, reduces the time of investigation process, strengthens the rapid reputation risk response principle, and is beneficial to making rapid and appropriate treatment in more time before public opinion fermentation of enterprises.
Description
Technical Field
The invention relates to the technical field of reputation risk management, in particular to a reputation risk positioning analysis method and system based on a risk positioning model.
Background
One of the principles of reputation risk management is quick response, but the amount of information related to public sentiment events is large, the evolution speed is high, and the risk of reputation risk upgrade exists in overlong investigation time and the reputation risk is evolved into a major reputation event. Meanwhile, the internet media are complex in type, such as characters, videos and pictures, so that the difficulty of risk location based on manual work is high, the time is long, and the principle of quick response of reputation risk management is violated. These factors make it difficult to implement reputation risk management quickly and accurately, and improvements are needed.
Disclosure of Invention
In order to solve at least the technical problems in the background art, the invention provides a reputation risk localization analysis method and system based on a risk localization model.
The invention provides a reputation risk positioning analysis method based on a risk positioning model, which is applied to the risk positioning model, wherein the risk positioning model comprises a retrieval frame and a data model; the method comprises the following steps:
the retrieval frame acquires public opinion research data, and the public opinion research data is associated with a specified public opinion main object; analyzing the public opinion research and judgment data to complete the positioning of the stakeholders and the positioning of the event cause-effect relationship;
the data model outputs the investigation result of the public opinion event based on the association rule of the interest relatives and the event causal relationship.
Further, before the search framework analyzes the public opinion research and judgment data, the method further comprises:
and carrying out preliminary judgment and filtering on the public opinion research and judgment data in a manual mode.
Further, the search framework accomplishes the location of stakeholders, including:
the locating of the stakeholder is accomplished by at least one of user portrayal, benefits system, screenshot searching, and blame.
Further, the search framework accomplishes the location of stakeholders, including:
manually establishing a user portrait knowledge graph, collecting internal user labels including name, gender, occupation, age group, region, head portrait and voiceprint multi-dimensional labels of a user, and establishing a user portrait feature database;
inputting the collected public opinion research and judgment data to carry out manual query and comparison, and outputting a user label of a public opinion event;
the stakeholder candidates are located according to the tag groupings.
Further, the retrieval framework accomplishes the location of event causality, including:
establishing an event cause and effect analysis view of basic information, benefit related information, compliance related information, risk related information and service interaction related information, establishing an event cause and effect view model, and establishing an event cause and effect relation database;
inputting the public opinion research and judgment data, and manually researching and judging by combining a causal relationship view provided by a system;
and outputting a positioning causal relation and a public opinion event causal view.
Further, the retrieval framework accomplishes the location of event causality, including:
summarizing basic information, benefit related information, compliance related information, risk related information and service interaction information into a cause relation document library;
inputting the public opinion research and judgment data to perform text similarity analysis and establish an index;
and outputting a positioning causal relation and a public opinion event causal view.
Further, the retrieval framework accomplishes the location of event causality, including:
inputting the public opinion research and judgment data;
establishing an event cause and effect relationship map according to the event cause and effect relationship database;
establishing a causal relationship derivation model, and deriving the collected public opinion research and judgment data according to event causal relationship;
and outputting a causal relationship view of the event.
The invention provides a reputation risk localization analysis system based on a risk localization model, which comprises an acquisition module, a processing module and a storage module, wherein the acquisition module is used for acquiring a reputation risk; the processing module is connected with the acquisition module and the storage module;
the storage module is used for storing executable computer program codes;
the acquisition module is used for acquiring public opinion research and judgment data and transmitting the public opinion research and judgment data to the processing module;
the processing module is configured to execute the method according to any one of the preceding claims by calling the executable computer program code in the storage module.
A third aspect of the present invention provides an electronic device comprising: a memory storing executable program code; a processor coupled with the memory; the processor calls the executable program code stored in the memory to perform the method of any of the preceding claims.
A fourth aspect of the invention provides a computer storage medium having stored thereon a computer program which, when executed by a processor, performs the method as set out in any one of the preceding claims.
In the scheme of the invention, the reputation risk positioning is modeled, the problems of high difficulty and long time of traditional manual review are solved, the time of the investigation process is reduced, the rapid reputation risk response principle is strengthened, and the method is favorable for rapidly and appropriately processing more time before the enterprise ferments due to public sentiment.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic flowchart of a reputation risk localization analysis method based on a risk localization model according to an embodiment of the present disclosure;
FIG. 2 is a schematic structural diagram of a reputation risk localization analysis system based on a risk localization model according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and "a plurality" typically includes at least two.
It should be understood that the term "and/or" as used herein is merely a relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
It should be understood that while the terms first, second, third, etc. may be used in the present embodiments to describe … …, these … … should not be limited to these terms. These terms are used only to distinguish … …. For example, a first … … may also be referred to as a second … …, and similarly, a second … … may also be referred to as a first … …, without departing from the scope of embodiments of the present application.
The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (a stated condition or event)" may be interpreted as "upon determining" or "in response to determining" or "upon detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)", depending on the context.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of additional like elements in a commodity or system comprising the element.
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a schematic flowchart of a reputation risk localization analysis method based on a risk localization model according to an embodiment of the present invention. As shown in fig. 1, a reputation risk localization analysis method based on a risk localization model according to an embodiment of the present invention is applied to a risk localization model, where the risk localization model includes a retrieval framework and a data model; the method comprises the following steps:
the retrieval frame acquires public opinion research data, and the public opinion research data is associated with a specified public opinion main object; analyzing the public opinion research and judgment data to complete the positioning of the stakeholders and the positioning of the event cause-effect relationship;
the data model outputs the investigation result of the public opinion event based on the association rule of the interest relatives and the event causal relationship.
In the embodiment of the invention, different from other algorithm models, the risk positioning model in the invention consists of a retrieval framework and a data model and is used for retrieving information and organizing necessary information required for coping with reputation risks.
The retrieval framework is because in an application scenario, the obtained data information may be incomplete or fuzzy, so that risk localization cannot be achieved simply by querying conditions, and thus the former way is performed manually. The risk localization model of the invention can determine the interest correlators and the event cause and effect relationship through other characteristics. The data model can output the investigation result of the public opinion event based on the association rule of the interest relatives and the event causal relationship, such as organizing and displaying the reason, fact and course of reputation risk, determining risk response measures, observing the risk response effect and the like.
The scheme of the invention models the reputation risk positioning, solves the problems of high difficulty and long time of traditional manual examination, reduces the time of investigation process, strengthens the rapid reputation risk response principle, and is beneficial to making rapid and appropriate treatment in more time before public opinion fermentation of enterprises.
Further, before the search framework analyzes the public opinion research and judgment data, the method further comprises:
and carrying out preliminary judgment and filtering on the public opinion research and judgment data in a manual mode.
In the embodiment of the invention, for external public opinion research and judgment data, preliminary judgment and filtration are manually carried out to remove obvious interference data, so that the reliability of input data of a risk positioning model is improved.
Further, the retrieval framework accomplishes the locating of stakeholders, including:
the locating of the stakeholder is accomplished by at least one of user portrayal, benefits system, screenshot searching, and blame.
Further, the search framework accomplishes the location of stakeholders, including:
manually establishing a user portrait knowledge map, collecting internal user labels including multi-dimensional labels of name, gender, occupation, age group, region, head portrait and voiceprint of a user, and establishing a user portrait characteristic database;
inputting the collected public opinion research and judgment data to perform manual query and comparison, and outputting a user label of a public opinion event;
the stakeholder candidates are located from the label packet.
In the embodiment of the invention, in the step of locating the stakeholders of the reputation risk location model, a user portrait method is introduced to locate the stakeholder candidates.
Further, the retrieval framework accomplishes the locating of stakeholders, including:
establishing a user portrait derivation model, which comprises a name derivation model, a occupation derivation model and an age derivation model;
inputting the collected public opinion research and judgment data to carry out AI derivation mapping, and outputting a user label of a public opinion event;
the stakeholder candidates are located according to the tag groupings.
In the embodiment of the invention, on the basis of the scheme, the manual query comparison part can be optimized, and the AI technology is adopted, so that the manual time is saved.
Further, the retrieval framework accomplishes the locating of stakeholders, including:
manually establishing an internal public opinion motivation dimension model, and establishing a public opinion motivation characteristic database;
presetting a plurality of major interest dry system scenes;
determining a interest affiliate list corresponding to the interest affiliate scene;
and inputting the public opinion research and judgment data, and outputting the interest related person candidates through the interest relation person list of the scene.
In the embodiment of the invention, in the step of positioning the stakeholders of the reputation risk positioning model, a stakeholder candidate is positioned by introducing a profit relationship method.
Further, the search framework accomplishes the location of stakeholders, including:
establishing an internal graph standard model, and establishing an internal graph standard library;
setting a graph standard classification rule;
inputting the public opinion research and judgment data, and manually screening and filtering the collected graphic characteristics;
a search query is created for the filtered graphical features, outputting the stakeholder candidates.
In the embodiment of the invention, in the step of positioning the stakeholders of the reputation risk positioning model, a screenshot searching method is introduced to position the stakeholder candidates.
Further, the search framework accomplishes the location of stakeholders, including:
carrying out manual name derivation on public opinion attack points possibly caused by system, system own loopholes and omission in internal control, compliance, risk, business and service, and creating an internal interest correlator database;
inputting the public opinion research and judgment data to inquire the corresponding feature data of the interest correlators;
and outputting the stakeholder candidates.
In the embodiment of the invention, in the step of locating the stakeholders of the reputation risk location model, the candidates of the stakeholders attributed to the locating of the stakeholders are introduced.
Further, the retrieval framework accomplishes the location of event causality, including:
establishing an event cause and effect analysis view of basic information (such as name, ID, address and the like), benefit related information (such as data of taking a position, trading and the like), compliance related information (such as business handling traces, appropriateness management information and the like), risk related information (such as liquidity risk, market risk and other change data) and service interaction related information (such as customer service records, records and the like), establishing an event cause and effect view model, and establishing an event cause and effect relation database;
inputting the public opinion research and judgment data, and manually researching and judging by combining a causal relationship view provided by a system;
and outputting a positioning causal relation and a public opinion event causal view.
In embodiments of the invention, event causality is relocated after completion of stakeholder location.
Further, the retrieval framework accomplishes the location of event causality, including:
summarizing basic information, benefit related information, compliance related information, risk related information and service interaction information into a cause relation document library;
inputting the public opinion research and judgment data to perform text similarity analysis and establish an index;
and outputting a positioning cause-and-effect relation and a public opinion event cause-and-effect view.
In the embodiment of the invention, on the basis of the scheme, the manual judging part is optimized, and the manual time can be saved by adopting a text similarity search method.
Further, the retrieval framework accomplishes the positioning of event causality, including:
inputting the public opinion research and judgment data;
establishing an event cause and effect relationship map according to the event cause and effect relationship database;
establishing a causal relationship derivation model, and deriving the collected public opinion research and judgment data according to event causal relationship;
and outputting a causal relationship view of the event.
In the embodiment of the invention, on the basis of the scheme, the manual judging part is optimized, and the NLP technology can be adopted to save time for causal positioning of manual events.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a reputation risk localization analysis system based on a risk localization model according to an embodiment of the present disclosure. As shown in fig. 2, a reputation risk localization analysis system based on a risk localization model according to an embodiment of the present invention includes an obtaining module 101, a processing module 102, and a storage module 103; the processing module 102 is connected with the obtaining module 101 and the storage module 103;
the storage module 103 is used for storing executable computer program codes;
the acquisition module 101 is configured to acquire public opinion research and judgment data and transmit the public opinion research and judgment data to the processing module 102;
the processing module 102 is configured to execute the method according to any one of the preceding items by calling the executable computer program code in the storage module 103.
The specific functions of the reputation risk localization analysis system based on the risk localization model in this embodiment refer to the above-described embodiment, and since the system in this embodiment adopts all the technical solutions of the above-described embodiment, at least all the beneficial effects brought by the technical solutions of the above-described embodiment are achieved, and are not described in detail herein.
Referring to fig. 3, fig. 3 is an electronic device according to an embodiment of the present invention, including: a memory storing executable program code; a processor coupled with the memory; the processor calls the executable program code stored in the memory to execute the method according to the previous embodiment.
The embodiment of the invention also discloses a computer storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the method of the embodiment is executed.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It should be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in more detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention.
Claims (10)
1. A reputation risk localization analysis method based on a risk localization model is characterized in that: the method is applied to a risk localization model, wherein the risk localization model comprises a retrieval frame and a data model; the method comprises the following steps:
the retrieval frame acquires public opinion studying and judging data, and the public opinion studying and judging data is associated with a specified public opinion main object; analyzing the public opinion research and judgment data to complete the positioning of the stakeholders and the positioning of the event cause-effect relationship;
the data model outputs the investigation result of the public sentiment event based on the association rule of the causal relationship between the stakeholders and the event.
2. The risk localization model-based reputation risk localization analysis method according to claim 1, wherein: before the retrieval framework analyzes the public opinion research data, the method further comprises the following steps:
and carrying out preliminary judgment and filtering on the public opinion research and judgment data in a manual mode.
3. The risk localization model-based reputation risk localization analysis method according to claim 1, wherein: the retrieval framework accomplishes the location of stakeholders, including:
locating the stakeholders is accomplished by at least one of user portrayal, benefits affiliation, screenshot searching, and blame attribution.
4. The risk localization model-based reputation risk localization analysis method according to claim 3, wherein: the retrieval framework accomplishes the location of stakeholders, including:
manually establishing a user portrait knowledge graph, collecting internal user labels including name, gender, occupation, age group, region, head portrait and voiceprint multi-dimensional labels of a user, and establishing a user portrait feature database;
inputting the collected public opinion research and judgment data to carry out manual query and comparison, and outputting a user label of a public opinion event;
the stakeholder candidates are located according to the tag groupings.
5. The risk localization model-based reputation risk localization analysis method according to claim 1, wherein: the retrieval framework completes the positioning of event causal relationship, and comprises the following steps:
establishing an event cause and effect analysis view of basic information, benefit related information, compliance related information, risk related information and service interaction related information, establishing an event cause and effect view model, and establishing an event cause and effect relation database;
inputting the public opinion research and judgment data, and manually researching and judging by combining a causal relationship view provided by a system;
and outputting a positioning causal relation and a public opinion event causal view.
6. The risk localization model-based reputation risk localization analysis method according to claim 1, wherein:
the retrieval framework completes the positioning of event causal relationship, and comprises the following steps:
summarizing basic information, benefit related information, compliance related information, risk related information and service interaction information into a cause relation document library;
inputting the public opinion research and judgment data to perform text similarity analysis and establish an index;
and outputting a positioning causal relation and a public opinion event causal view.
7. The risk localization model-based reputation risk localization analysis method according to claim 1, wherein:
the retrieval framework completes the positioning of event causal relation, and comprises the following steps:
inputting the public opinion research and judgment data;
establishing an event cause and effect relationship map according to the event cause and effect relationship database;
establishing a causal relationship derivation model, and deriving the collected public opinion research and judgment data according to event causal relationship;
and outputting a causal relationship view of the event.
8. A reputation risk positioning analysis system based on a risk positioning model comprises an acquisition module, a processing module and a storage module; the processing module is connected with the acquisition module and the storage module;
the storage module is used for storing executable computer program codes;
the acquisition module is used for acquiring public opinion research and judgment data and transmitting the public opinion research and judgment data to the processing module;
the method is characterized in that: the processing module for executing the method according to any one of claims 1-7 by calling the executable computer program code in the storage module.
9. An electronic device, comprising: a memory storing executable program code; a processor coupled with the memory; the method is characterized in that: the processor calls the executable program code stored in the memory to perform the method of any of claims 1-7.
10. A computer storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, performs the method of any one of claims 1-7.
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| CN202211401169.9A CN115907465A (en) | 2022-11-09 | 2022-11-09 | Reputation risk positioning analysis method and system based on risk positioning model |
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