CN110909227A - Method and device for analyzing news value degree - Google Patents
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Abstract
The invention discloses a method and a device for analyzing news value degree, wherein the method comprises the following steps: obtaining an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials; analyzing the value degree of the news material by utilizing the evaluation parameter set; the first type of parameters is positively correlated with the value degree of news materials, and the second type of parameters is negatively correlated with the value degree of the news materials. The influence of the factors of the news material publisher on the value degree analysis of the news is eliminated, and the accuracy and the efficiency of the value degree analysis of the news are improved, so that a user can timely and accurately find the material with the news value by using a self-media platform, and the timeliness and the accuracy of the news are guaranteed.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for analyzing news value.
Background
The propagation media of news contents include various categories such as televisions, broadcasts, newspapers, magazines, new internet media and the like, and in recent years, the new internet media are developed rapidly from a media platform (such as a microblog), so that the news frequency preempts the first opportunity in the reports of hot news.
The news content is very timeliness, and if the news content cannot preempt the first opportunity and master valuable news materials, the news content is output on a starting line of news production. Therefore, how to utilize information distribution platforms (such as various self-media platforms) on the internet to timely and accurately mine news and timely obtain high-value news materials distributed on the information distribution platforms becomes a problem to be solved urgently by each media.
Disclosure of Invention
In view of the above problems, the present application is provided to provide a method and an apparatus for analyzing news value, which overcome or at least partially solve the above problems, and can help each media to timely and accurately obtain news material with high value from each information distribution platform.
The method for analyzing the news value degree provided by the embodiment of the application comprises the following steps:
obtaining an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters are positively correlated with the value degree of the news materials, and the second type of parameters are negatively correlated with the value degree of the news materials.
Optionally, the first type of parameter includes any one or more of a forwarding amount, an evaluation amount, and an approval amount; the second type of parameters includes fan size and/or amount of interest of the publisher of the news material.
Optionally, the analyzing the value degree of the news material by using the evaluation parameter set specifically includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first class parameter to the influence degree of the brush amount; or the sub-value degree is the ratio of the sum of each calibration value to the influence degree of the brush amount; the calibration value is obtained according to the first type of parameters and the corresponding weight.
Optionally, the analyzing the value degree of the news material by using the evaluation parameter set specifically includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
and obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brushing influence degree.
Optionally, the obtaining the total popularity of the news material according to each of the first type parameters and the obtaining the brushing volume influence of the news material according to each of the second type parameters specifically includes:
for each first parameter, obtaining a first value by using the weight corresponding to the first parameter, and determining the sum of each obtained first value as the total heat;
and for each second parameter, obtaining a second value by using the corresponding weight, and determining the sum of each obtained second value as the brush amount influence degree.
The device of analysis news price degree that this application embodiment provided, the device includes: an acquisition unit and an evaluation unit;
the acquisition unit is used for acquiring an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
the evaluation unit is used for analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters are positively correlated with the value degree of the news materials, and the second type of parameters are negatively correlated with the value degree of the news materials.
Optionally, the first type of parameter includes any one or more of a forwarding amount, an evaluation amount, and an approval amount; the second type of parameters includes fan size and/or amount of interest of the publisher of the news material.
Optionally, the evaluation unit specifically includes: a processing subunit and an evaluation subunit;
the processing subunit is configured to obtain the total heat of the news material according to each of the first type parameters, and obtain the brushing effect degree of the news material according to each of the second type parameters;
the evaluation subunit is used for obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first class parameter to the influence degree of the brush amount; or the sub-value degree is the ratio of the sum of each calibration value to the influence degree of the brush amount; the calibration value is obtained according to the first type of parameters and the corresponding weight.
Optionally, the evaluation unit specifically includes: a processing subunit and an evaluation subunit;
the processing subunit is configured to obtain the total heat of the news material according to each of the first type parameters, and obtain the brushing effect degree of the news material according to each of the second type parameters;
and the evaluation subunit is used for obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brushing influence degree.
Optionally, the processing subunit specifically includes: a first subunit and a second subunit;
the first subunit is configured to, for each first parameter, obtain a first value by using a weight corresponding to the first parameter, and determine a sum of each obtained first value as the total heat;
and the second subunit is configured to, for each second parameter, obtain a second value by using the weight corresponding to the second parameter, and determine a sum of each obtained second value as the brush amount influence degree.
An embodiment of the present application also provides a storage medium having a program stored thereon, where the program, when executed by a processor, implements any one of the methods of analyzing news worth degrees provided by the above embodiments.
The embodiment of the present application further provides a processor, where the processor is configured to execute a program, where the program executes any one of the methods for analyzing news worth degrees provided in the foregoing embodiments when running.
By means of the technical scheme, the method and the device for analyzing the news value are characterized in that the evaluation parameter set of the news materials is obtained from the target platform, the first type of parameters reflecting the popularity of the news materials and the second type of parameters reflecting the popularity of the publisher of the news materials are used for analyzing the value of the news materials, the data of all aspects of the news materials are comprehensively considered to reflect the value of the news materials, the influence of factors of the publisher of the news materials on the analysis of the own value of the news is eliminated, the accuracy and the efficiency of the analysis of the news value are improved, and therefore a user can timely and accurately find the materials with the news value by using the media platform, and the timeliness and the accuracy of news are guaranteed.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart illustrating a method for analyzing news value according to an embodiment of the present disclosure;
FIG. 2 is a flow chart illustrating another method for analyzing news worthiness provided by an embodiment of the present application;
FIG. 3 is a flow chart illustrating a further method for analyzing news ratings according to an embodiment of the present application;
FIG. 4 is a diagram illustrating an analysis of news ratings with only first type parameters;
FIG. 5 is a diagram illustrating news worth degree obtained by a method for analyzing news worth degree provided by an embodiment of the application;
fig. 6 shows a schematic structural diagram of an apparatus for analyzing news value provided in an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The news content is very timeliness, and if the news content cannot preempt the first opportunity and master valuable news materials, the news content is output on a starting line of news production. However, the number of reporters of any one media is limited, the range of activities, time and energy of the reporters are limited, and all news clues cannot be timely and comprehensively obtained. The best news material channel can more conveniently acquire the news material of the first hand, so that many media are focused on various information publishing platforms (such as self-media platforms) on the Internet at present.
News clues are discovered on an internet information publishing platform, time efficiency is very important, and media need to master news materials at the first time when or before news contents are fermented, so that the news clues have high reporting value. However, many new contents are released every day on the information release platform, and the efficiency of screening the meat of the reporter by only media is very low, which is not beneficial to timely and accurately exploring news materials.
Therefore, the method and the device for analyzing the news value degree provided by the embodiment of the application can analyze the news value degree of the news material by using various information of the news material on the information distribution platform, simplify the workload of a media reporter for searching the news material with high value and excellent content, and ensure the timeliness and accuracy of news.
For ease of understanding, a specific application scenario of the embodiments of the present application is first introduced. The method and the device for analyzing the news value degree are used for mining news materials with high value from various information publishing platforms on the Internet. The information publishing platform includes, but is not limited to, the following: self-media platforms such as microblog, hundred family number, wechat public number, Facebook (Facebook), Twitter (Twitter), and multimedia distribution platforms such as video and music. For convenience of description, the method and the apparatus for analyzing news worth degree provided by the embodiment of the present application are described in detail below by taking a microblog as an example, and the implementation manners of other scenarios are similar to this, and are not repeated here.
Based on the above-mentioned ideas, in order to make the above-mentioned objects, features and advantages of the present application more comprehensible, specific embodiments of the present application are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, the figure is a schematic flowchart of a method for analyzing news value provided in an embodiment of the present application.
The method for analyzing the news worth degree provided by the embodiment of the application comprises the steps S101-S102.
S101: and obtaining an evaluation parameter set of news materials released on the target platform.
It is to be appreciated that the target platform may be published by publishers of various types of information including, but not limited to, text, video, audio, and the like. The target platform may be any one of the above examples of various information publishing platforms on the internet, and the embodiment of the present application is not limited. News materials refer to various contents published by publishers on a self-media platform, and taking a micro-blog platform as an example, the news materials can be micro-blogs published by various publishers.
In the embodiment of the application, the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publishers of the news materials. The higher the popularity of a general news material is, the higher the value of the news material is, namely the news value is, but as the data of the news material, such as the forwarding amount, the evaluation amount, the forwarding amount and the like, which reflect the popularity of the news material, are influenced by the popularity and the attention degree of a publisher, more people can possibly forward, evaluate and forward the news material when seeing the news material, the information published by the publisher with a large number of fans is generally more than the information published by the publisher with a small number of fans regardless of whether the content of the information is good or not and whether the content of the information has the news value, and the accuracy is lower only by taking the first type parameter reflecting the popularity of the news material as the basis for evaluating the popularity of the news material.
Continuing to take the microblog platform as an example, a microblog issued by a publisher is forwarded, commented and paid by other people who watch the microblog, and the number of the operations reflects the popularity and the attention degree of the microblog (i.e. news material), but the number of fans of the publisher also affects the number of the operations, and only the forwarding amount, the comment amount and the attention degree are taken as evaluation bases of the value, so that the accuracy of the value evaluation is affected due to the fact that the popularity and the attention degree of the publisher are too high. For example, a simple personal opinion microblog issued by a star generally has no news value, but due to a lot of fans of the star, the forwarding amount, the comment amount and the like of the released microblog are often very high, so that the popularity of the microblog issued by the star is very high, and if only the forwarding amount, the comment amount and the like are taken as evaluation bases of the value degree, the news value degree of the microblog per se cannot be reflected very well.
Therefore, in order to avoid the influence of the popularity and the concerned degree of the publisher on the analysis of the news value and the content quality, in the embodiment of the application, a second parameter reflecting the popularity of the news material publisher is introduced and is also used as a basis for evaluating the news material value, so that the influence of the popularity and the concerned degree of the publisher on the analysis of the news value is eliminated, and the accuracy of the analysis of the news material value is improved.
In a specific scenario, as an example, the first type parameter may include any one or more of a forwarding amount, an evaluation amount, and an approval amount; the second type of parameters may include fan size and/or amount of interest to the publisher of the news material.
S102: and analyzing the value degree of the news material by utilizing the evaluation parameter set.
In the embodiment of the application, generally, the higher the popularity of the news material is, the higher the news value thereof is, and the popularity of the publisher is not beneficial to the analysis of the content of the news material, so that when the popularity of the news material is analyzed by utilizing the evaluation parameter set, the first type of parameters is positively correlated with the popularity of the news material, and the second type of parameters is negatively correlated with the popularity of the news material, so as to ensure the accuracy of the analysis of the popularity and the content quality degree of the news material. In the following, how to analyze the worth of the news material by using the evaluation parameter set will be described in detail with reference to specific situations, which is not repeated herein.
In the embodiment of the application, the evaluation parameter set of the news materials is obtained from the media platform, the first type of parameters reflecting the popularity of the news materials and the second type of parameters reflecting the popularity of the publishers of the news materials are used for analyzing the value of the news materials, the reflection of all aspects of data of the news materials on the value is comprehensively considered, the influence of factors of the publishers of the news materials on the value analysis of the news is eliminated, the accuracy and the efficiency of the news value analysis are improved, and therefore a user can timely and accurately find the materials with the news value by using the media platform, and the timeliness and the accuracy of the news are guaranteed.
In some possible implementations of the embodiment of the present application, the step S102 has at least the following two possible implementations, which are described below one by one.
In a first possible implementation manner, as shown in fig. 2, step S102 may specifically include:
s201: and obtaining the total heat of the news materials according to each first type of parameter, and obtaining the brushing influence degree of the news materials according to each second type of parameter.
S202: obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material; and the sub-value degree is the ratio of the sum of each first type parameter to the influence degree of the brush amount.
It is understood that when there is only one first type parameter, the first type parameter is the total popularity of the news material, and in practical applications, when there are multiple first type parameters, the sum or average value of each first type parameter may be used as the total popularity of the news material. Similarly, when the second type of parameter is only one, the second type of parameter is the brushing volume influence degree of the news material; when there are a plurality of second-type parameters, the sum or average value of each second-type parameter may be used as the brushing influence degree of the news material. The embodiment of the application does not limit the specific implementation manner of how to obtain the total heat of the news material according to each first-class parameter and how to obtain the brushing influence degree of the news material according to each second-class parameter.
Taking a microblog platform as an example, when the first type of parameters include a forwarding amount R, an evaluation amount C and a praise amount a, and the second type of parameters include a vermicelli amount F, the value V of news materials can be obtained specifically according to the following formula (1):
the fan base numbers of a plurality of microblog issuers are very large, the issued microblogs are relatively simple to obtain high heat, and the brushing rate of forwarding, evaluating and praising is higher, so that the microblogs with large fan amount and high heat cannot explain that the content of the microblogs is high in quality and value. Just there are many microblog issuers, their own fans are not large, because the content of the microblogs issued by the fans is high in quality and the news value is high, and the influence of each fan on the popularity of the microblogs is multiplied. Therefore, in the embodiment of the application, the vermicelli quantity index is introduced, the influence of the vermicelli base number on the hot degree of the microblog content is reduced intentionally, and the average hot degree level (namely the sub-value degree) of the microblog in the vermicelli is calculated so as to reflect the high quality degree and the spreading value of the microblog content.
It should also be noted that in practical applications, audiences are more inclined to perform different operations on a piece of news material according to the degree of interest of the audience due to the different difficulty and influence on the piece of news material. For example, for the microblog, praise is simple and does not affect the account number of a praise, so that the user can praise the microblog content more easily; the forwarded information can be issued to the microblog number of the forwarder, and the operation is complex, so that the psychological defense line of the user is higher, and compared with the praise possibility, the probability is low; the comment needs to be written with a plurality of characters to express the own view, and is one of the most difficult users to execute. Therefore, in order to further improve the accuracy of news worth degree analysis, in some possible implementation manners of the embodiment of the present application, a corresponding weight may be set for each parameter in the evaluation parameter set in advance, and the weights of the parameters are comprehensively considered when analyzing the worth degree of the news material.
Specifically, in some possible implementation manners, step S201 may specifically include:
for each first parameter, obtaining a first value by using the weight corresponding to the first parameter, and determining the sum of each obtained first value as the total heat; and for each second parameter, obtaining a second value by using the corresponding weight, and determining the sum of each obtained second value as the influence degree of the brush amount.
In specific implementation, the corresponding weights can be set for different parameters according to the difficulty of various operations and the user psychology, and the specific setting rule of the weights is not limited in the embodiment of the application.
Continuing to take the microblog platform as an example, when the first type of parameters include the forwarding amount R, the evaluation amount C and the like, and the second type of parameters include the vermicelli amount F, the formula (1) can be transformed into the formula (2) by adding the weight:
in the formula, kR、kC、kAAnd kFRespectively as forwarding amount R, evaluation amount C and praiseThe weight corresponding to the amount A and the fan amount F. In one example, kR、kC、kAAnd kFAnd may be 0.2, 0.4, 0.2, and 0.2, respectively.
In some possible implementations, the sub-value degree may also be a ratio of the sum of each calibration value to the degree of influence of the brush amount; the calibration value is obtained according to the first type parameter and the corresponding weight. As an example, the sub-value degree can be specifically obtained according to the following formula (3):
in the formula, kR、kC、kAAnd kFThe weights are respectively corresponding to the forwarding amount R, the evaluation amount C, the praise amount A and the fan amount F.
In a second possible implementation manner, as shown in fig. 3, step S102 may specifically include:
s301: and obtaining the total heat of the news materials according to each first type of parameter, and obtaining the brushing influence degree of the news materials according to each second type of parameter.
S302: and obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brush quantity influence degree.
It is to be understood that, similar to the first possible implementation manner, when there is only one first-type parameter, the first-type parameter is the total popularity of the news material, and in practical applications, when there are multiple first-type parameters, the sum or average value of each first-type parameter may be used as the total popularity of the news material. Similarly, when the second type of parameter is only one, the second type of parameter is the brushing volume influence degree of the news material; when there are a plurality of second-type parameters, the sum or average value of each second-type parameter may be used as the brushing influence degree of the news material. The embodiment of the application does not limit the specific implementation manner of how to obtain the total heat of the news material according to each first-class parameter and how to obtain the brushing influence degree of the news material according to each second-class parameter.
Taking a microblog platform as an example, when the first type of parameters include a forwarding amount R, an evaluation amount C and a praise amount a, and the second type of parameters include a vermicelli amount F, the value V of news materials can be obtained specifically according to the following formula (4):
similar to the first possible implementation manner, in order to further improve the accuracy of news worth degree analysis, in some possible implementation manners of the embodiment of the present application, a corresponding weight may also be set for each parameter in the evaluation parameter set in advance, and the weights of the parameters are comprehensively considered when analyzing the worth degree of the news material.
Specifically, in some possible implementation manners, step S301 may specifically include:
for each first parameter, obtaining a first value by using the weight corresponding to the first parameter, and determining the sum of each obtained first value as the total heat; and for each second parameter, obtaining a second value by using the corresponding weight, and determining the sum of each obtained second value as the influence degree of the brush amount.
Continuing taking the microblog platform as an example, when the first type of parameters comprise the forwarding amount R, the evaluation amount C and the praise amount A, and the second type of parameters comprise the vermicelli amount F, the formula (4) can be transformed into the formula (5) after the weight is added:
in the formula, kR、kC、kAAnd kFThe weights are respectively corresponding to the forwarding amount R, the evaluation amount C, the praise amount A and the fan amount F. In one example, kR、kC、kAAnd kFAnd may be 0.2, 0.4, 0.2, and 0.2, respectively. It can be understood that the setting manner of the weight is similar to that of the first possible implementation manner, and specific reference may be made to the above related description, which is not described herein again.
In order to make the advantages of the embodiments of the present application more apparent, a specific example is described below.
Referring to fig. 4, an example of analyzing the value of the microblog based on only the first type of parameter is shown. As can be seen from fig. 4, the microblogs arranged in front are basically the same several microblog numbers, and the microblogs in front are almost released by the microblog numbers with high fan number except for the basic high heat. Therefore, the number of fans can influence the accuracy of the microblog value degree analysis, and the accurate acquisition of news is not facilitated. Fig. 5 shows an example of analyzing the popularity of a microblog by using the news popularity analysis method provided by the embodiment of the application. Different microblog numbers appear in fig. 5, and some microblog value degrees are ranked at the top, but the number of fans of the microblog numbers is only hundreds or dozens, so that the influence of the number of fans on the evaluation of the microblog contents can be eliminated.
Comparing fig. 4 and fig. 5, fig. 4 shows only one content of the topic related to the image of the burner, but fig. 5 shows 4 contents of the topic related to the image of the burner, wherein 3 contents cannot be ranked to the front position because of low number of fans of the contents, but when acquiring news materials, it is exactly stated that such contents are concerned, have high quality and are more valuable and potential.
Based on the news value analysis method provided by the embodiment, the embodiment of the application further provides a news value analysis device.
Referring to fig. 6, this figure is a schematic structural diagram of an apparatus for analyzing news value provided in an embodiment of the present application.
The device of analysis news price degree that this application embodiment provided includes: an acquisition unit 100 and an evaluation unit 200;
the acquisition unit 100 is configured to acquire an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
the evaluation unit 200 is used for analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters is positively correlated with the value degree of news materials, and the second type of parameters is negatively correlated with the value degree of the news materials.
In some possible implementation manners of the embodiment of the present application, the first type parameter may include any one or more of a forwarding amount, an evaluation amount, and a like amount; the second type of parameters may include fan size and/or amount of interest to the publisher of the news material.
In some possible implementation manners of the embodiment of the present application, the evaluation unit 200 may specifically include: a processing subunit and an evaluation subunit;
the processing subunit is used for obtaining the total heat of the news materials according to each first type of parameter and obtaining the brushing influence degree of the news materials according to each second type of parameter;
the evaluation subunit is used for obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first type parameter to the influence degree of the brush amount; or, the sub-value degree is the ratio of the sum of each calibration value and the influence degree of the brush amount; the calibration value is obtained according to the first type parameter and the corresponding weight.
In some possible implementation manners of the embodiment of the present application, the evaluation unit 200 may specifically include: a processing subunit and an evaluation subunit;
the processing subunit is used for obtaining the total heat of the news materials according to each first type of parameter and obtaining the brushing influence degree of the news materials according to each second type of parameter;
and the evaluation subunit is used for obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brush amount influence degree.
In some possible implementation manners of the embodiment of the present application, the processing subunit 100 may specifically include: a first subunit and a second subunit;
the first subunit is used for obtaining a first value for each first parameter by using the corresponding weight of the first parameter, and determining the sum of each obtained first value as the total heat degree;
and the second subunit is used for obtaining a second value for each second parameter by using the corresponding weight, and determining the sum of each obtained second value as the brush quantity influence degree.
In the embodiment of the application, the evaluation parameter set of the news materials is obtained from the media platform, the first type of parameters reflecting the popularity of the news materials and the second type of parameters reflecting the popularity of the publishers of the news materials are used for analyzing the value of the news materials, the reflection of all aspects of data of the news materials on the value is comprehensively considered, the influence of factors of the publishers of the news materials on the value analysis of the news is eliminated, the accuracy and the efficiency of the news value analysis are improved, and therefore a user can timely and accurately find the materials with the news value by using the media platform, and the timeliness and the accuracy of the news are guaranteed.
The device for analyzing the news worth degree comprises a processor and a memory, wherein the acquisition unit, the evaluation unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more than one, and the kernel parameters are adjusted to help each media to timely and accurately obtain news materials with high value from each information publishing platform.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
An embodiment of the present application provides a storage medium on which a program is stored, the program implementing any one of the methods of analyzing news worth degrees provided by the above embodiments when executed by a processor.
The embodiment of the present application provides a processor, where the processor is configured to execute a program, where the program executes any one of the methods for analyzing news worth degrees provided in the foregoing embodiments when running.
The embodiment of the application provides equipment, the equipment comprises a processor, a memory and a program which is stored on the memory and can run on the processor, and the following steps are realized when the processor executes the program:
obtaining an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters are positively correlated with the value degree of the news materials, and the second type of parameters are negatively correlated with the value degree of the news materials.
Optionally, the first type of parameter includes any one or more of a forwarding amount, an evaluation amount, and an approval amount; the second type of parameters includes fan size and/or amount of interest of the publisher of the news material.
Optionally, the analyzing the value degree of the news material by using the evaluation parameter set specifically includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first class parameter to the influence degree of the brush amount; or the sub-value degree is the ratio of the sum of each calibration value to the influence degree of the brush amount; the calibration value is obtained according to the first type of parameters and the corresponding weight.
Optionally, the analyzing the value degree of the news material by using the evaluation parameter set specifically includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
and obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brushing influence degree.
Optionally, the obtaining the total popularity of the news material according to each of the first type parameters and the obtaining the brushing volume influence of the news material according to each of the second type parameters specifically includes:
for each first parameter, obtaining a first value by using the weight corresponding to the first parameter, and determining the sum of each obtained first value as the total heat;
and for each second parameter, obtaining a second value by using the corresponding weight, and determining the sum of each obtained second value as the brush amount influence degree.
The device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device:
obtaining an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters are positively correlated with the value degree of the news materials, and the second type of parameters are negatively correlated with the value degree of the news materials.
Optionally, the first type of parameter includes any one or more of a forwarding amount, an evaluation amount, and an approval amount; the second type of parameters includes fan size and/or amount of interest of the publisher of the news material.
Optionally, the analyzing the value degree of the news material by using the evaluation parameter set specifically includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first class parameter to the influence degree of the brush amount; or the sub-value degree is the ratio of the sum of each calibration value to the influence degree of the brush amount; the calibration value is obtained according to the first type of parameters and the corresponding weight.
Optionally, the analyzing the value degree of the news material by using the evaluation parameter set specifically includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
and obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brushing influence degree.
Optionally, the obtaining the total popularity of the news material according to each of the first type parameters and the obtaining the brushing volume influence of the news material according to each of the second type parameters specifically includes:
for each first parameter, obtaining a first value by using the weight corresponding to the first parameter, and determining the sum of each obtained first value as the total heat;
and for each second parameter, obtaining a second value by using the corresponding weight, and determining the sum of each obtained second value as the brush amount influence degree.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of analyzing news ratings, the method comprising:
obtaining an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters are positively correlated with the value degree of the news materials, and the second type of parameters are negatively correlated with the value degree of the news materials.
2. The method according to claim 1, wherein the first type parameters include any one or more of forwarding amount, evaluation amount and approval amount; the second type of parameters includes fan size and/or amount of interest of the publisher of the news material.
3. The method according to claim 2, wherein the analyzing the newsfeed by the set of evaluation parameters includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first class parameter to the influence degree of the brush amount; or the sub-value degree is the ratio of the sum of each calibration value to the influence degree of the brush amount; the calibration value is obtained according to the first type of parameters and the corresponding weight.
4. The method according to claim 2, wherein the analyzing the newsfeed by the set of evaluation parameters includes:
obtaining the total heat of the news materials according to each first type parameter, and obtaining the brushing influence degree of the news materials according to each second type parameter;
and obtaining the value degree of the news material by utilizing the ratio of the total heat degree to the brushing influence degree.
5. The method according to claim 3 or 4, wherein the obtaining of the total popularity of the news material according to each of the first type parameters and the obtaining of the influence of the brushing amount of the news material according to each of the second type parameters specifically comprises:
for each first parameter, obtaining a first value by using the weight corresponding to the first parameter, and determining the sum of each obtained first value as the total heat;
and for each second parameter, obtaining a second value by using the corresponding weight, and determining the sum of each obtained second value as the brush amount influence degree.
6. An apparatus for analyzing news value degree, the apparatus comprising: an acquisition unit and an evaluation unit;
the acquisition unit is used for acquiring an evaluation parameter set of news materials released on a target platform; the evaluation parameter set comprises a first type of parameters reflecting the popularity of the news materials and a second type of parameters reflecting the popularity of the publisher of the news materials;
the evaluation unit is used for analyzing the value degree of the news material by using the evaluation parameter set; the first type of parameters are positively correlated with the value degree of the news materials, and the second type of parameters are negatively correlated with the value degree of the news materials.
7. The apparatus according to claim 6, wherein the first type parameters include any one or more of forwarding amount, evaluation amount and approval amount; the second type of parameters includes fan size and/or amount of interest of the publisher of the news material.
8. The device according to claim 7, wherein the evaluation unit comprises: a processing subunit and an evaluation subunit;
the processing subunit is configured to obtain the total heat of the news material according to each of the first type parameters, and obtain the brushing effect degree of the news material according to each of the second type parameters;
the evaluation subunit is used for obtaining the value degree of the news material according to the total popularity and the sub-value degree of the news material;
wherein the sub-value degree is the ratio of the sum of each first class parameter to the influence degree of the brush amount; or the sub-value degree is the ratio of the sum of each calibration value to the influence degree of the brush amount; the calibration value is obtained according to the first type of parameters and the corresponding weight.
9. A storage medium having stored thereon a program which, when executed by a processor, implements a method of analyzing news worth values as claimed in any one of claims 1 to 5.
10. A processor, characterized in that the processor is configured to run a program, wherein the program when running performs the method of analyzing newsfeed as claimed in any one of claims 1 to 5.
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