CN110569475A - Evaluation method, device, equipment and storage medium for netizen influence - Google Patents
Evaluation method, device, equipment and storage medium for netizen influence Download PDFInfo
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- CN110569475A CN110569475A CN201910885293.9A CN201910885293A CN110569475A CN 110569475 A CN110569475 A CN 110569475A CN 201910885293 A CN201910885293 A CN 201910885293A CN 110569475 A CN110569475 A CN 110569475A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
Abstract
The embodiment of the invention discloses a method, a device, equipment and a storage medium for evaluating netizen influence. Wherein, the method comprises the following steps: calculating the grade of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant; and evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters. The technical scheme provided by the embodiment of the invention provides a comprehensive reference standard for evaluating the netizen influence in different network platforms, solves the problem of excessively large evaluation system in the prior art, and simplifies the evaluation process of the network influence.
Description
Technical Field
The embodiment of the invention relates to the technical field of internet information management, in particular to a method, a device, equipment and a storage medium for evaluating netizen influence.
Background
with the rapid development of internet technology, various network applications such as news, social media or live broadcast software are applied more and more widely in daily life of people, so as to provide various entertainment messages, music, news or videos and other information for netizens. Because the audience of the network application is wide, authority degrees of different netizens in the network application are different, and different opinions also exist for information such as a certain event or service execution condition published in the network application, when determining public opinions in the network application, influence of the netizens in the network application needs to be evaluated first.
At present, when the netizen influence in network application is evaluated, a corresponding evaluation system is preset for each related network application, and different evaluation systems are adopted to calculate the netizen influence in different network applications, so that the evaluation system is too large, the reference standard of the netizen influence cannot be effectively integrated, and the evaluation process is complicated.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for evaluating netizen influence, which provide a comprehensive reference standard for netizen influence in a network platform and simplify the evaluation process.
in a first aspect, an embodiment of the present invention provides a method for evaluating netizen influence, where the method includes:
Calculating the grade of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant;
and evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
In a second aspect, an embodiment of the present invention provides an evaluation apparatus for netizen influence, where the apparatus includes:
the score calculation module is used for calculating the score of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant;
and the influence evaluation module is used for evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
In a third aspect, an embodiment of the present invention provides an apparatus, where the apparatus includes:
One or more processors;
A storage device for storing one or more programs,
When the one or more programs are executed by the one or more processors, the one or more processors implement the evaluation method for netizen influence according to any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the evaluation method for netizen influence according to any embodiment of the present invention.
The embodiment of the invention provides a method, a device, equipment and a storage medium for evaluating influence of netizens, wherein different influence parameters, reference constants corresponding to the influence parameters and evaluation coefficients of a network platform are set on different network platforms, the influence of the netizens on the network platform is evaluated by acquiring specific values of the influence parameters of the netizens on the network platform and analyzing the correlation degree between the specific values and the corresponding reference constants to obtain scores of the influence parameters, and then the influence of the netizens on the network platform is evaluated by combining the evaluation coefficients on the network platform and the scores of the influence parameters, so that a comprehensive reference standard is provided for evaluation of the influence of the netizens in different network platforms, the problem of too large evaluation system in the prior art is solved, and the evaluation process of the influence of the network is simplified.
drawings
other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
fig. 1 is a flowchart of a method for evaluating netizen influence according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for evaluating netizen influence according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an evaluation apparatus for network influence according to a third embodiment of the present invention;
Fig. 4 is a schematic structural diagram of an apparatus according to a fourth embodiment of the present invention.
Detailed Description
the present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a method for evaluating netizen influence according to an embodiment of the present invention. The evaluation method for netizen influence provided by this embodiment may be executed by the evaluation device for netizen influence provided by the embodiment of the present invention, and the device may be implemented in a software and/or hardware manner and integrated in a device for executing the method.
specifically, referring to fig. 1, the method specifically includes the following steps:
And S110, calculating the grade of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant.
When analyzing a certain situation such as a news event or service execution published in the network platform, the network platform may need to acquire real and objective opinions expressed by most netizens in the network platform so as to perform accurate operation through the real and objective public opinions in the following; at this time, in the embodiment, the trueness and objectivity of each netizen opinion in the network platform are judged through netizen influence, and the netizen influence belongs to a newly created reference dimension relative to the existing internet information analysis scene, so that the accuracy of internet information analysis is ensured.
specifically, the influence parameter in this embodiment refers to operation data that has a certain influence on the reality and objectivity of the netizen opinion in each operation activity performed by the netizen on various internet information published in the network platform, such as the number of comments, the number of forwarding, and the like of the netizen on the network platform; in this embodiment, different impact parameters are preset on each network platform, and a value of a reference constant corresponding to each impact parameter on each network platform is estimated according to a comprehensive history value and a corresponding ratio of each impact parameter in different network platforms.
optionally, when evaluating the influence of the netizen on the network platform, first, a specific value of each influence parameter preset on the network platform by the netizen needs to be obtained, a value of a reference constant corresponding to each influence parameter on the network platform is found, and then, a score of the netizen on the network platform relative to each influence parameter is calculated by respectively judging a correlation degree, namely a difference degree between the specific value of each influence parameter and the value of the reference constant corresponding to the influence parameter.
for example, the following formula can be used to calculate the score of the impact parameter in this embodiment:
wherein score (factor, t) is the score of the influence parameter, factor is the specific value of the influence parameter, and t is the reference constant corresponding to the influence parameter; different factors in the network platform correspond to different t.
at this time, the reference constant t is a constant value preset for each influence parameter in the network platform, so in this embodiment, only the specific value of each influence parameter of the netizen in the network platform needs to be obtained, and the score of each influence parameter is calculated by using the above formula.
and S120, evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
the evaluation coefficient on the network platform refers to factors that influence the influence of the netizens on different network platforms as the netizens are different or the network platforms are different, such as whether the netizens obtain official certification of the network platforms or weights among the network platforms.
in this embodiment, after the score of each influence parameter of the netizen on the network platform is obtained, the score of each influence parameter is comprehensively analyzed according to different influence degrees caused by each influence parameter on the influence of the netizen, and then the overall score caused by the influence parameter of the netizen on the network platform is further adjusted by using the preset evaluation coefficient on the network platform, so that the influence of the netizen on the network platform is accurately evaluated.
for example, in this embodiment, the evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of the different influence parameters may specifically include: weighting and summing the scores of different influence parameters on the network platform to obtain a comprehensive score of the netizen on the network platform; and adjusting the comprehensive score through the evaluation coefficient on the network platform to obtain the influence of the netizen on the network platform.
Specifically, in this embodiment, the weights of the influence parameters may be predefined according to different influence degrees of the influence parameters on the netizen on the network platform, and when performing comprehensive analysis on the scores of the influence parameters, the scores of the different influence parameters on the network platform are directly calculated in a weighted summation manner to obtain a comprehensive score of the netizen on the network platform; subsequently, the evaluation coefficient on the network platform is adopted to further adjust the comprehensive score so as to accurately obtain the influence of the netizen on the network platform.
for example, the following formula can be used to calculate the influence of the netizen on the network platform in this embodiment:
Wherein influence is the influence of the netizen on the network platform, Eval is an evaluation coefficient set on the network platform, and can be whether the netizen obtains official certification of the network platform or a weight value between the network platforms, and ξiScore corresponding to each influence parameter set on the network platformi(factor, t) is the score of the impact parameters on the network platform, and i is the number of the impact parameters on the network platform.
On the basis of the above technical solution, after the influence of the netizen on the network platform is evaluated, the method may further include: and analyzing the public opinion of the netizens on the network platform according to the influence of the netizens on the network platform.
Specifically, after obtaining the influence of the netizens on the network platform, the embodiment may screen out the netizens with higher influence according to the influence of a plurality of netizens on the same network platform, where the screened netizens are more authoritative, real and objective users on the network platform, and subsequently obtain the public opinion of the netizens on the network platform by analyzing the whole opinion of the screened netizens on information such as a certain event or service execution condition issued on the network platform.
In addition, in this embodiment, the preference degree of the same netizen for each network platform can be determined according to the influence of the netizen on different network platforms.
According to the technical scheme provided by the embodiment, different influence parameters, reference constants corresponding to the influence parameters and evaluation coefficients of the network platforms are set on different network platforms, specific values of the influence parameters of the netizen on the network platforms are collected, the association degree between the specific values and the corresponding reference constants is analyzed, scores of the influence parameters are obtained, the influence of the netizen on the network platforms is evaluated by subsequently combining the evaluation coefficients on the network platforms and the scores of the influence parameters, a comprehensive reference standard is further provided for evaluation of the influence of the netizen on the different network platforms, the problem that an evaluation system in the prior art is too large is solved, and the evaluation process of the influence of the network is simplified.
Example two
Fig. 2 is a flowchart of an evaluation method for netizen influence according to a second embodiment of the present invention. The embodiment of the invention is optimized on the basis of the embodiment. Optionally, the present embodiment explains the impact parameters and the evaluation coefficients set on the network platform in detail.
Specifically, referring to fig. 2, the method of this embodiment may specifically include:
S210, obtaining the influence parameters of the netizen on the network platform according to the type of the network platform.
Specifically, because the audience quantities of the developed network platforms are different, the information traffic and platform scales of different network platforms are different, and the type of each network platform can be determined according to the information traffic and platform scale of the network platform; in this embodiment, a network platform with larger information flow and platform scale and more influence parameters related to netizens is used as a first type of network platform, such as a microblog; and compared with the first type of network platform, the network platform with smaller information flow and platform scale enables the network platform with less influence parameters related to netizens to be used as the second type of network platform.
At this time, the embodiment may further obtain different types of impact parameters set on the network platform according to the type of the network platform by analyzing the type of the network platform, so as to obtain a specific value and a corresponding reference constant of each impact parameter on the network platform by the netizen in the following.
For example, in this embodiment, the influence parameters on the first type of network platform may be preset to include a posting amount (PostCount), a forwarding amount (RepostCount), a comment amount (commenting count) and a fan number (FanCount) of the netizen on the network platform, and the influence parameters on the second type of network platform include a posting amount (PostCount) and a comment amount (commenting count) of the netizen on the network platform.
And S220, calculating the grade of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant.
And S230, carrying out weighted summation on the scores of different influence parameters on the network platform to obtain the comprehensive score of the netizen on the network platform.
And S240, adjusting the comprehensive score through the evaluation coefficient on the network platform to obtain the influence of the netizens on the network platform.
Specifically, in this embodiment, according to the type of the network platform, the evaluation coefficient on the first type of network platform may also be set as an authentication parameter of the netizen on the network platform, and the evaluation coefficient on the second type of network platform is a weight coefficient of the network platform in the second type.
For example, for a first type of network platform, if a netizen passes authentication of the first type of network platform, an evaluation coefficient (authentication parameter) of the first type of network platform with respect to the netizen is set to a first set value, such as 100; if the netizen fails to pass the authentication of the first type of network platform, the evaluation coefficient (authentication parameter) of the first type of network platform with respect to the netizen is set to a second set value, such as 90. For the second type of network platform, a corresponding weight value may be set for each network platform in the second type according to the importance degree of each network platform in the second type, and the weight value may be used as an evaluation coefficient of the second type of network platform.
At this time, since the information flow and the platform scale of the first type of network platform are large, the influence parameter on the network platform is too large, and thus the influence parameter is located at a different magnitude from the set reference constant, which results in too large calculation data amount and small difference of netizen influence force, and therefore, the embodiment may further include: and if the network platform is of the first type, determining that the influence parameters of the netizen on the network platform are positioned under the magnitude of the corresponding reference constant.
specifically, in this embodiment, a logarithmic function may be used to perform magnitude conversion on the specific value of each influence parameter of the netizen on the first type of network platform, so that the accuracy of the score of each influence parameter is ensured when the influence parameter of the netizen on the network platform is converted to the magnitude of the corresponding reference constant.
For example, the calculation formula of netizen influence in the first type of network platform in this embodiment may be as follows:
influence＝AuthAccount*[0.3*score(factor＝ln(PostCount+1)*10,t＝5000)
+0.2*score(factor＝ln(RepostCount+1)*10,t＝60000)
+0.3*score(factor＝ln(CommentCount+1)*10,t＝20000)
+0.2*score(factor＝ln(FanCount+1)*10,t＝70000)]；
Wherein AuthAccount is an authentication parameter of netizens in the first type of network platform, the passing authentication is 100, and the failing authentication is 90; ln (PostCount +1) × 10 is the magnitude conversion result of the posting volume of the netizen in the first type of network platform, ln (RepostCount +1) is the magnitude conversion result of the posting volume of the netizen in the first type of network platform, ln (CommentCount +1) × 10 is the magnitude conversion result of the comment volume of the netizen in the first type of network platform, ln (FanCount +1) × 10 is the magnitude conversion result of the number of fans of the netizen in the first type of network platform.
On the contrary, because the information flow and the platform scale of the second type of network platform are small, and the specific value of the impact parameter on the network platform is also low, the magnitude conversion of the impact parameter in the second type of network platform is not needed, and at this time, the calculation formula of the netizen impact in the second type of network platform may be as follows:
influence＝WebsiteWeight*[0.6*score(factor＝PostCount,t＝100)
+0.4*score(factor＝CommentCount,t＝100)]；
here, websitewight is an evaluation coefficient (weight coefficient) of each network platform in the second type.
in addition, it should be noted that, when a new network platform is subsequently developed, the influence of the netizen on the newly developed network platform may also be calculated by setting the influence parameters, the corresponding reference constants, and the evaluation coefficients on the newly developed network platform by using the method provided in this embodiment.
and S250, analyzing the public opinion of the netizen on the network platform according to the influence of the netizen on the network platform.
according to the technical scheme provided by the embodiment, different influence parameters, reference constants corresponding to the influence parameters and evaluation coefficients of the network platforms are set on different network platforms, specific values of the influence parameters of the netizen on the network platforms are collected, the association degree between the specific values and the corresponding reference constants is analyzed, scores of the influence parameters are obtained, the influence of the netizen on the network platforms is evaluated by subsequently combining the evaluation coefficients on the network platforms and the scores of the influence parameters, a comprehensive reference standard is further provided for evaluation of the influence of the netizen on the different network platforms, the problem that an evaluation system in the prior art is too large is solved, and the evaluation process of the influence of the network is simplified.
EXAMPLE III
Fig. 3 is a schematic structural diagram of an apparatus for evaluating network influence according to a third embodiment of the present invention, as shown in fig. 3, the apparatus may include:
The score calculating module 310 is configured to calculate a score of the influence parameter according to a correlation degree between the influence parameter of the netizen on the network platform and the corresponding reference constant;
and the influence evaluation module 320 is used for evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
According to the technical scheme provided by the embodiment, different influence parameters, reference constants corresponding to the influence parameters and evaluation coefficients of the network platforms are set on different network platforms, specific values of the influence parameters of the netizen on the network platforms are collected, the association degree between the specific values and the corresponding reference constants is analyzed, scores of the influence parameters are obtained, the influence of the netizen on the network platforms is evaluated by subsequently combining the evaluation coefficients on the network platforms and the scores of the influence parameters, a comprehensive reference standard is further provided for evaluation of the influence of the netizen on the different network platforms, the problem that an evaluation system in the prior art is too large is solved, and the evaluation process of the influence of the network is simplified.
Further, the influence evaluation module 320 may be specifically configured to:
Weighting and summing the scores of different influence parameters on the network platform to obtain a comprehensive score of the netizen on the network platform;
And adjusting the comprehensive score through the evaluation coefficient on the network platform to obtain the influence of the netizens on the network platform.
Further, the evaluation apparatus for netizen influence may further include:
and the influence parameter determining module is used for acquiring the influence parameters of the netizen on the network platform according to the type of the network platform, and the type of the network platform is determined by the information flow of the network platform and the platform scale.
Further, the influence parameters on the first type of network platform may include the posting amount, forwarding amount, comment amount and fan number of netizens on the network platform;
The influence parameters on the second type of network platform may include the posting amount and the comment amount of netizens on the network platform;
The evaluation coefficient on the first type of network platform is the authentication parameter of the netizen on the network platform;
The evaluation coefficient on the second type of network platform is a weighting coefficient of the network platform under the second type.
Further, the evaluation apparatus for netizen influence may further include:
And the magnitude determination module is used for determining that the influence parameters of the netizen on the network platform are under the magnitude of the corresponding reference constant if the network platform is of the first type.
Further, the evaluation apparatus for netizen influence may further include:
and the public opinion analyzing module is used for analyzing the netizen public opinions on the network platform according to the influence of the netizen on the network platform.
the evaluation device for netizen influence provided by the embodiment can be applied to the evaluation method for netizen influence provided by any of the above embodiments, and has corresponding functions and beneficial effects.
Example four
Fig. 4 is a schematic structural diagram of an apparatus according to a fourth embodiment of the present invention. As shown in fig. 4, the apparatus comprises a processor 40, a storage means 41 and a communication means 42; the number of processors 40 in the device may be one or more, and one processor 40 is taken as an example in fig. 4; the processor 40, the storage means 41 and the communication means 42 of the device may be connected by a bus or other means, as exemplified by the bus connection in fig. 4.
the storage device 41 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and modules, such as modules corresponding to the evaluation method for netizen influence in the embodiment of the present invention (for example, the score calculation module 310 and the influence evaluation module 320 in the evaluation device for netizen influence). The processor 40 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the storage device 41, that is, the evaluation method of netizen influence described above is realized.
the storage device 41 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage device 41 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 41 may further include memory located remotely from processor 40, which may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The communication device 42 may be used to implement a network connection or a mobile data connection.
The device provided by the embodiment can be used for executing the evaluation method for netizen influence provided by any embodiment, and has corresponding functions and beneficial effects.
EXAMPLE five
Fifth, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, can implement the evaluation method for netizen influence in any of the above embodiments.
The method specifically comprises the following steps:
Calculating the grade of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant;
And evaluating the influence of the netizens on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the operations of the method described above, and may also perform related operations in the evaluation method for netizen influence provided by any embodiment of the present invention.
from the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the evaluation apparatus for netizen influence, the included units and modules are only divided according to the functional logic, but are not limited to the above division as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for evaluating netizen influence is characterized by comprising the following steps:
calculating the grade of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant;
And evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
2. The method of claim 1, wherein the evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters comprises:
weighting and summing the scores of different influence parameters on the network platform to obtain a comprehensive score of the netizen on the network platform;
And adjusting the comprehensive score through the evaluation coefficient on the network platform to obtain the influence of the netizen on the network platform.
3. the method of claim 1, wherein before calculating the score of the impact parameter according to the correlation between the impact parameter of the netizen on the network platform and the corresponding reference constant, further comprises:
and acquiring the influence parameters of the netizen on the network platform according to the type of the network platform, wherein the type of the network platform is determined by the information flow and the platform scale of the network platform.
4. The method of claim 3, wherein the impact parameters on the first type of network platform include the amount of posting, the amount of forwarding, the amount of comments, and the number of fans of the netizen on the network platform;
The influence parameters on the second type of network platform comprise the posting amount and the comment amount of the netizen on the network platform;
The evaluation coefficient on the first type of network platform is an authentication parameter of the netizen on the network platform;
And the evaluation coefficient on the second type of network platform is a weight coefficient of the network platform under the second type.
5. the method of claim 3, further comprising:
And if the network platform is of the first type, determining that the influence parameters of the netizen on the network platform are positioned under the magnitude of the corresponding reference constant.
6. the method according to any one of claims 1-5, further comprising, after evaluating the influence of the netizen on the network platform:
And analyzing the public opinion of the netizens on the network platform according to the influence of the netizens on the network platform.
7. An evaluation device for netizen influence, comprising:
The score calculation module is used for calculating the score of the influence parameter according to the association degree between the influence parameter of the netizen on the network platform and the corresponding reference constant;
And the influence evaluation module is used for evaluating the influence of the netizen on the network platform according to the evaluation coefficient on the network platform and the scores of different influence parameters.
8. the apparatus of claim 7, wherein the impact assessment module is specifically configured to:
Weighting and summing the scores of different influence parameters on the network platform to obtain a comprehensive score of the netizen on the network platform;
And adjusting the comprehensive score through the evaluation coefficient on the network platform to obtain the influence of the netizen on the network platform.
9. An apparatus, characterized in that the detection apparatus comprises:
one or more processors;
A storage device for storing one or more programs,
When executed by the one or more processors, cause the one or more processors to implement the method for assessing netizen's influence of any one of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the evaluation method of netizen's influence according to any one of claims 1-6.
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| CN111428204A (en) * | 2020-06-12 | 2020-07-17 | 深圳大数据计算机信息股份有限公司 | Credit system construction method and system based on block chain decentralization |
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