CN111340531A - Method, device, computer storage medium and terminal for realizing brand analysis - Google Patents
Method, device, computer storage medium and terminal for realizing brand analysis Download PDFInfo
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Abstract
A method, a device, a computer storage medium and a terminal for realizing brand analysis comprise: obtaining brand related information of a brand to be analyzed from social public opinion data; and determining the fondness information of the brand to be analyzed according to the acquired related information of the brand. Wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data. According to the embodiment of the invention, the analysis of the love information is realized through the social public opinion data, and the analysis efficiency and accuracy of the love information are improved.
Description
Technical Field
The present disclosure relates to, but not limited to, information analysis technologies, and more particularly, to a method, an apparatus, a computer storage medium, and a terminal for implementing brand analysis.
Background
The popularity (also called brand love (brand) reflects the popularity of the brand of consumers, and is an important index of brand health. Currently, the determination of the love degree is mainly carried out by adopting a questionnaire investigation mode; the questionnaire investigation timeliness is low, the investigation range is limited, and a comprehensive and accurate analysis result cannot be obtained. With the development of the brand of the young people, how to effectively monitor the information of the popularity of the brand of the young people becomes a technical problem to be solved.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
The embodiment of the invention provides a method, a device, a computer storage medium and a terminal for realizing brand analysis, which can improve the analysis efficiency and accuracy of the preference degree information.
The embodiment of the invention provides a method for realizing brand analysis, which comprises the following steps:
obtaining brand related information of a brand to be analyzed from social public opinion data;
determining the fondness information of the brand to be analyzed according to the acquired related information of the brand;
wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data.
In an exemplary embodiment, the determining the popularity information of the brand to be analyzed includes:
converting each brand related information of the brand to be analyzed into corresponding index information;
and multiplying a preset index weighting coefficient by each corresponding index information, and accumulating to obtain the preference information.
In an exemplary embodiment, when the brand-related information includes a mutual amount, the converting each brand-related information of the brand to be analyzed into corresponding index information includes:
calculating index information Y of the mutual quantity of the brand to be analyzed on each platform through the following formula1：
Y1＝100+(X1-AVERAGE1)/(MAX1–MIN1)*100；
Multiplying a preset first platform weighting coefficient of each platform with corresponding index information of the mutual amount, and accumulating to obtain the index information of the mutual amount of the brand to be analyzed;
wherein, X is1The interaction quantity value of the brand to be analyzed on the platform is obtained; the AVERAGE1The average value of the interaction quantity values of two or more brands in the platform is obtained; the MAX1The maximum value of the interaction quantity value in two or more brands in the platform; the MIN1Is the minimum value of the mutual quantity value in two or more brands in the platform.
In an exemplary embodiment, when the brand related information includes volume, the converting each brand related information of the brand to be analyzed into corresponding index information includes:
calculating the index information Y of the sound volume of the brand to be analyzed on each platform through the following formula2：
Y2＝100+(X2-AVERAGE2)/(MAX2–MIN2)*100；
Multiplying a preset second platform weighting coefficient by corresponding acoustic quantity index information, and accumulating to obtain acoustic quantity index information of the brand to be analyzed;
wherein, X2The sound volume value of the brand to be analyzed on the platform; AVERAGE2The average value of the sound volume values of two or more brands in the platform is obtained; MAX2The maximum value of the sound volume numerical value in two or more brands in the platform; MIN2Is the minimum value of the sound volume values in two or more brands in the platform.
In an exemplary embodiment, when the brand-related information includes positive and negative emotion data, the converting each brand-related information of the brand to be analyzed into corresponding index information includes:
counting the positive and negative emotion surface data to obtain positive and negative emotion surface post statistical information;
calculating index information corresponding to positive and negative emotion data according to the obtained statistical information of positive and negative emotion posts:
(number of posts with all platforms containing positive emotion words-number of posts with all platforms containing negative emotion words)/(number of posts with all platforms containing positive emotion words + number of posts with all platforms containing negative emotion words) × 100;
(the number of posts of all platform emotion positive words + the number of posts of all platforms which do not contain emotion positive and negative words)/the total number of posts contained in all platform emotion positive and negative data is 100;
the total number of posts of all platforms containing the positive emotion words/the total number of posts contained in the positive emotion face data and the negative emotion face data of all platforms is 100;
calculating index information Y of the emotion positive and negative surface data of the brand to be analyzed on each platform through the following formula3：Y3＝100+(X3-AVERAGE3)/(MAX3–MIN3) 100, x; multiplying a preset third platform weighting coefficient by index information of corresponding emotion positive and negative surface data, and accumulating to obtain the index information of the sound volume of the brand to be analyzed;
wherein the positive and negative emotion post statistics comprise one or any combination of the following: all platforms contain the post number of positive emotion words, all platforms contain the post number of negative emotion words, all platforms do not contain the post number of positive emotion words, all platforms contain the total post number in negative emotion data, each platform contains the post number of positive emotion words, and each platform contains the post number of negative emotion words; said X3Scoring the positive and negative emotion surfaces of the brand to be analyzed on the current platform; the AVERAGE3The average value of the emotion positive and negative scores of two or more brands in the current platform is obtained; the MAX3The maximum value of the emotion positive and negative surface scores in two or more brands in the current platform is obtained; the MIN3The minimum value of the positive and negative scores of the emotion in two or more brands in the current platform is obtained; the positive and negative emotion scores comprise scores obtained by the following formula: (number of posts the current platform contains positive emotion words-number of posts the current platform contains negative emotion words)/(number of posts the current platform contains positive emotion words + number of posts the current platform contains negative emotion words) × 100.
In an exemplary embodiment, after obtaining the brand related information of the brand to be analyzed, the method further includes:
and performing dewatering treatment on the acquired information related to the brand.
On the other hand, the embodiment of the present invention further provides a computer storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements the method for implementing brand analysis.
In another aspect, an embodiment of the present invention further provides a terminal, including: a memory and a processor, the memory having a computer program stored therein; wherein the content of the first and second substances,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of implementing brand analysis as described above.
In another aspect, an embodiment of the present invention further provides an apparatus for implementing brand analysis, including: an acquisition unit and a determination unit; wherein the content of the first and second substances,
the acquisition unit is used for: obtaining brand related information of a brand to be analyzed from social public opinion data;
the determination unit is used for: determining the fondness information of the brand to be analyzed according to the acquired related information of the brand;
wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data.
In an exemplary embodiment, the determining unit is specifically configured to:
converting each brand related information of the brand to be analyzed into corresponding index information;
and multiplying a preset index weighting coefficient by each corresponding index information, and accumulating to obtain the preference information.
Compared with the related art, the technical scheme of the application comprises the following steps: obtaining brand related information of a brand to be analyzed from social public opinion data; and determining the fondness information of the brand to be analyzed according to the acquired related information of the brand. Wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data. According to the embodiment of the invention, the analysis of the love information is realized through the social public opinion data, and the analysis efficiency and accuracy of the love information are improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the example serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a flow chart of a method of implementing brand analysis in accordance with an embodiment of the present invention;
fig. 2 is a block diagram of an apparatus for implementing brand analysis according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
The steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.
Fig. 1 is a flowchart of a method for implementing brand analysis according to an embodiment of the present invention, as shown in fig. 1, including:
wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data.
In an exemplary embodiment, the amount of interaction includes, but is not limited to, one or any combination of the following: forwarding number, praise number, comment number.
It should be noted that the mutual quantity of the embodiments of the present invention may be an accumulation of forwarding numbers, praise numbers, and/or comment numbers.
In an exemplary embodiment, the sound volume includes, but is not limited to: the amount of searches on the platform for brand-related keywords.
In an exemplary embodiment, the brand related information may be information within a preset time period; for example, a month from the first time. The preset duration can be analyzed and determined according to the type of the brand, the location, the product use period and the like. The brand related information may be sampling information, for example, a certain amount of sample data is extracted at a set time interval after acquiring historical data of a long period or a large data amount, and the sample data is used as the brand related information.
It should be noted that the social public opinion data in the embodiment of the present invention may include data obtained by a related technology.
And 102, determining the fondness information of the brand to be analyzed according to the acquired related information of the brand.
In an exemplary embodiment, the determining the popularity information of the brand to be analyzed includes:
converting each brand related information of the brand to be analyzed into corresponding index information;
and multiplying a preset index weighting coefficient by each corresponding index information, and accumulating to obtain the preference information.
In an exemplary embodiment, according to The pre-stored score information of The importance degree of each kind of brand related information, The embodiment of The present invention may obtain The exponential weighting coefficient of each brand related information through an Analytic Hierarchy Process (AHP); AHP is a qualitative and quantitative combined, systematic, hierarchical analytical method in the correlation technique, used for dealing with the complicated decision-making problem; it provides a measure of judgment consistency and simplifies the preference level in the decision criteria by a pairwise comparison.
It should be noted that the exponential weighting coefficient can be set empirically by those skilled in the art, and can be adjusted according to the output result.
In an exemplary embodiment, when the brand-related information includes a mutual amount, the converting each brand-related information of the brand to be analyzed into corresponding index information includes:
calculating index information Y of the mutual quantity of the brand to be analyzed on each platform through the following formula1：
Y1＝100+(X1-AVERAGE1)/(MAX1–MIN1)*100；
Multiplying a preset first platform weighting coefficient of each platform with corresponding index information of the mutual amount, and accumulating to obtain the index information of the mutual amount of the brand to be analyzed;
wherein, X is1The interaction quantity value of the brand to be analyzed on the platform is obtained; the AVERAGE1The average value of the interaction quantity values of two or more brands in the platform is obtained; the MAX1The maximum value of the interaction quantity value in two or more brands in the platform; the MIN1Is the minimum value of the mutual quantity value in two or more brands in the platform.
It should be noted that the first platform weighting factor may be configured by analysis with reference to the result of the previous questionnaire adjustment, or may be set and adjusted by a person skilled in the art based on an empirical value. In addition, the embodiment of the invention can adopt other formulas to calculate the index information, and the value range of the index information obtained by general calculation is a positive number smaller than a preset value. For example, the exponent information is a positive number less than 200. The average value of the interaction quantity value can be calculated by those skilled in the art after performing brand screening according to a set rule.
In an exemplary embodiment, when the brand related information includes volume, the converting each brand related information of the brand to be analyzed into corresponding index information includes:
calculating the index information Y of the sound volume of the brand to be analyzed on each platform through the following formula2：
Y2＝100+(X2-AVERAGE2)/(MAX2–MIN2)*100；
Multiplying a preset second platform weighting coefficient by corresponding acoustic quantity index information, and accumulating to obtain acoustic quantity index information of the brand to be analyzed;
wherein, X2The sound volume value of the brand to be analyzed on the platform; AVERAGE2The average value of the sound volume values of two or more brands in the platform is obtained; MAX2The maximum value of the sound volume numerical value in two or more brands in the platform; MIN2Is the minimum value of the sound volume values in two or more brands in the platform.
It should be noted that the second platform weighting factor may be configured by analysis with reference to the result of the previous questionnaire adjustment, or may be set and adjusted by a person skilled in the art based on an empirical value. In addition, the embodiment of the invention can adopt other formulas to calculate the index information, and the value range of the index information obtained by general calculation is a positive number smaller than a preset value. For example, the exponent information is a positive number less than 200. The average value of the sound volume values can be calculated by those skilled in the art after performing brand screening according to set rules.
When the brand related information comprises positive and negative emotion data, converting each brand related information of the brand to be analyzed into corresponding index information, and the method comprises the following steps:
counting the positive and negative emotion surface data to obtain positive and negative emotion surface post statistical information;
calculating index information corresponding to positive and negative emotion data according to the obtained statistical information of positive and negative emotion posts:
(number of posts with all platforms containing positive emotion words-number of posts with all platforms containing negative emotion words)/(number of posts with all platforms containing positive emotion words + number of posts with all platforms containing negative emotion words) × 100;
(the number of posts of all platform emotion positive words + the number of posts of all platforms which do not contain emotion positive and negative words)/the total number of posts contained in all platform emotion positive and negative data is 100;
the total number of posts of all platforms containing the positive emotion words/the total number of posts contained in the positive emotion face data and the negative emotion face data of all platforms is 100;
calculating index information Y of the emotion positive and negative surface data of the brand to be analyzed on each platform through the following formula3：Y3＝100+(X3-AVERAGE3)/(MAX3–MIN3) 100, x; multiplying a preset third platform weighting coefficient by index information of corresponding emotion positive and negative surface data, and accumulating to obtain the index information of the sound volume of the brand to be analyzed;
wherein the positive and negative emotion post statistics comprise one or any combination of the following: all platforms contain the post number of positive emotion words, all platforms contain the post number of negative emotion words, all platforms do not contain the post number of positive emotion words, all platforms contain the total post number in negative emotion data, each platform contains the post number of positive emotion words, and each platform contains the post number of negative emotion words; said X3Scoring the positive and negative emotion surfaces of the brand to be analyzed on the current platform; the AVERAGE3The average value of the emotion positive and negative scores of two or more brands in the current platform is obtained; the MAX3The maximum value of the emotion positive and negative surface scores in two or more brands in the current platform is obtained; the MIN3The minimum value of the positive and negative scores of the emotion in two or more brands in the current platform is obtained; the positive and negative emotion scores comprise scores obtained by the following formula: (number of posts the current platform contains positive emotion words-number of posts the current platform contains negative emotion words)/(number of posts the current platform contains positive emotion words + number of posts the current platform contains negative emotion words) × 100.
In an exemplary embodiment, when the brand related information includes positive and negative emotion data, index information corresponding to the positive and negative emotion data may be calculated and obtained by referring to a related technology; for example, after word frequency statistics is carried out on positive and negative emotion data, word frequencies of the positive emotion data and the negative emotion data are counted; and converting to obtain index information with a positive value, wherein the value range of the index information is smaller than a preset value, according to the word frequency of the positive emotion data and the negative emotion data. For example, after the emotion positive and negative data are processed by referring to the related technology, when the obtained emotion score is a percentage value, the obtained percentage value can be directly multiplied by 100 to obtain corresponding index information;
assuming that the brand to be analyzed is brand A, calculating the obtained acoustic quantity index information, the mutual quantity index information and the emotion positive and negative surface data index information of the brand A according to the method provided by the embodiment of the invention, multiplying the preset index weighting coefficients by the corresponding index information according to the set acoustic quantity index weighting coefficients, the mutual quantity index weighting coefficients and the emotion positive and negative surface data index weighting coefficients, and accumulating to obtain the love degree information:
the preference degree information is the index information of the volume of sound of the brand A, the index weighting coefficient of the volume of sound, the index information of the mutual amount of the brand A, the index weighting coefficient of the mutual amount, the index information of the positive and negative emotion face data of the brand A, and the index weighting coefficient of the positive and negative emotion face data.
In an exemplary embodiment, after obtaining the brand related information of the brand to be analyzed, the method in the embodiment of the present invention further includes:
and performing dewatering treatment on the acquired information related to the brand.
It should be noted that the dewatering treatment can be performed by methods known in the related art, and will not be described herein.
In addition, the embodiment of the invention obtains the love information of a plurality of brands, and can realize the analysis of the brands by comparing the love information of the plurality of brands.
Compared with the related art, the technical scheme of the application comprises the following steps: obtaining brand related information of a brand to be analyzed from social public opinion data; and determining the fondness information of the brand to be analyzed according to the acquired related information of the brand. Wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data. According to the embodiment of the invention, the analysis of the love information is realized through the social public opinion data, and the analysis efficiency and accuracy of the love information are improved.
The embodiment of the invention also provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and when being executed by a processor, the computer program realizes the method for realizing the brand analysis.
An embodiment of the present invention further provides a terminal, including: a memory and a processor, the memory having a computer program stored therein; wherein the content of the first and second substances,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of implementing brand analysis as described above.
Fig. 2 is a block diagram of an apparatus for implementing brand analysis according to an embodiment of the present invention, as shown in fig. 2, including: an acquisition unit and a determination unit; wherein the content of the first and second substances,
the acquisition unit is used for: obtaining brand related information of a brand to be analyzed from social public opinion data;
wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data.
In an exemplary embodiment, the amount of interaction includes, but is not limited to, one or any combination of the following: forwarding number, praise number, comment number.
It should be noted that the mutual quantity of the embodiments of the present invention may be an accumulation of forwarding numbers, praise numbers, and/or comment numbers.
In an exemplary embodiment, the sound volume includes, but is not limited to: the amount of searches on the platform for brand-related keywords.
In an exemplary embodiment, the brand related information may be information within a preset time period; for example, a month from the first time. The preset duration can be analyzed and determined according to the type of the brand, the location, the product use period and the like. The brand related information may be sampling information, for example, a certain amount of sample data is extracted at a set time interval after acquiring historical data of a long period or a large data amount, and the sample data is used as the brand related information.
It should be noted that the social public opinion data in the embodiment of the present invention may include data obtained by a related technology.
The determination unit is used for: and determining the fondness information of the brand to be analyzed according to the acquired related information of the brand.
In an exemplary embodiment, the determining unit is specifically configured to:
converting each brand related information of the brand to be analyzed into corresponding index information;
and multiplying a preset index weighting coefficient by each corresponding index information, and accumulating to obtain the preference information.
It should be noted that the exponential weighting coefficient can be set empirically by those skilled in the art, and can be adjusted according to the output result.
In an exemplary embodiment, the determining unit is configured to convert each brand related information of the brand to be analyzed into corresponding index information, and includes:
when the brand related information comprises the mutual amount, index information Y of the mutual amount of the brand to be analyzed on each platform is calculated through the following formula1：Y1＝100+(X1-AVERAGE1)/(MAX1–MIN1) 100, x; multiplying a preset first platform weighting coefficient of each platform with corresponding index information of the mutual amount, and accumulating to obtain the index information of the mutual amount of the brand to be analyzed;
when the brand related information comprises the sound volume, the index information Y of the sound volume of the brand to be analyzed on each platform is calculated through the following formula2：Y2＝100+(X2-AVERAGE2)/(MAX2–MIN2) 100, x; weighting the preset second platformAfter the number is multiplied by the index information of the corresponding sound volume, accumulating to obtain the index information of the sound volume of the brand to be analyzed;
when the brand related information comprises positive and negative emotion data, counting the positive and negative emotion data to obtain positive and negative emotion post statistical information;
calculating index information corresponding to positive and negative emotion data according to the obtained statistical information of positive and negative emotion posts:
(number of posts with all platforms containing positive emotion words-number of posts with all platforms containing negative emotion words)/(number of posts with all platforms containing positive emotion words + number of posts with all platforms containing negative emotion words) × 100;
(the number of posts of all platform emotion positive words + the number of posts of all platforms which do not contain emotion positive and negative words)/the total number of posts contained in all platform emotion positive and negative data is 100;
the total number of posts of all platforms containing the positive emotion words/the total number of posts contained in the positive emotion face data and the negative emotion face data of all platforms is 100;
calculating index information Y of the emotion positive and negative surface data of the brand to be analyzed on each platform through the following formula3：Y3＝100+(X3-AVERAGE3)/(MAX3–MIN3) 100, x; multiplying a preset third platform weighting coefficient by index information of corresponding emotion positive and negative surface data, and accumulating to obtain the index information of the sound volume of the brand to be analyzed;
wherein, X1The interaction quantity value of the brand to be analyzed on the platform is obtained; AVERAGE1The average value of the interaction quantity values of two or more brands in the platform is obtained; MAX1The maximum value of the interaction quantity value in two or more brands in the platform; MIN1The minimum value of the interaction quantity value in two or more brands in the platform; x2The sound volume value of the brand to be analyzed on the platform; AVERAGE2The average value of the sound volume values of two or more brands in the platform is obtained; MAX2The maximum value of the sound volume numerical value in two or more brands in the platform; MIN2Two or more in the platformMinimum value of sound volume value in the brand. The statistical information of positive and negative posts of emotion comprises one or any combination of the following items: all platforms contain the post number of positive emotion words, all platforms contain the post number of negative emotion words, all platforms do not contain the post number of positive emotion words, all platforms contain the total post number in negative emotion data, each platform contains the post number of positive emotion words, and each platform contains the post number of negative emotion words; said X3Scoring the positive and negative emotion surfaces of the brand to be analyzed on the current platform; the AVERAGE3The average value of the emotion positive and negative scores of two or more brands in the current platform is obtained; the MAX3The maximum value of the emotion positive and negative surface scores in two or more brands in the current platform is obtained; the MIN3The minimum value of the positive and negative scores of the emotion in two or more brands in the current platform is obtained; the positive and negative emotion scores comprise scores obtained by the following formula: (number of posts the current platform contains positive emotion words-number of posts the current platform contains negative emotion words)/(number of posts the current platform contains positive emotion words + number of posts the current platform contains negative emotion words) × 100.
It should be noted that the first platform weighting factor may be configured by analysis with reference to the result of the previous questionnaire adjustment, or may be set and adjusted by a person skilled in the art based on an empirical value. In addition, the embodiment of the invention can adopt other formulas to calculate the index information, and the value range of the index information obtained by general calculation is a positive number smaller than a preset value. For example, the exponent information is a positive number less than 200. The average value of the interaction quantity value can be calculated by those skilled in the art after performing brand screening according to a set rule. The second platform weighting factor may be configured analytically with reference to the results of the previous questionnaire adjustments, or may be set and adjusted by those skilled in the art based on empirical values. In addition, the embodiment of the invention can adopt other formulas to calculate the index information, and the value range of the index information obtained by general calculation is a positive number smaller than a preset value. For example, the exponent information is a positive number less than 200. The average value of the sound volume values can be calculated by those skilled in the art after performing brand screening according to set rules.
In an exemplary embodiment, when the brand related information includes positive and negative emotion data, index information corresponding to the positive and negative emotion data may be calculated and obtained by referring to a related technology; for example, after word frequency statistics is carried out on positive and negative emotion data, word frequencies of the positive emotion data and the negative emotion data are counted; and converting to obtain index information with a positive value, wherein the value range of the index information is smaller than a preset value, according to the word frequency of the positive emotion data and the negative emotion data. For example, after the emotion positive and negative data are processed by referring to the related technology, when the obtained emotion score is a percentage value, the obtained percentage value can be directly multiplied by 100 to obtain corresponding index information;
in an exemplary embodiment, the apparatus further comprises a dewatering unit for:
and performing dewatering treatment on the acquired information related to the brand.
It should be noted that the dewatering treatment can be performed by methods known in the related art, and will not be described herein.
Compared with the related art, the technical scheme of the application comprises the following steps: obtaining brand related information of a brand to be analyzed from social public opinion data; and determining the fondness information of the brand to be analyzed according to the acquired related information of the brand. Wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data. According to the embodiment of the invention, the analysis of the love information is realized through the social public opinion data, and the analysis efficiency and accuracy of the love information are improved.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
Claims (10)
1. A method of implementing brand analysis, comprising:
obtaining brand related information of a brand to be analyzed from social public opinion data;
determining the fondness information of the brand to be analyzed according to the acquired related information of the brand;
wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data.
2. The method of claim 1, wherein determining the popularity information for the brand to be analyzed comprises:
converting each brand related information of the brand to be analyzed into corresponding index information;
and multiplying a preset index weighting coefficient by each corresponding index information, and accumulating to obtain the preference information.
3. The method according to claim 2, wherein when the brand-related information includes an amount of interaction, the converting each brand-related information of the brand to be analyzed into corresponding index information includes:
calculating index information Y of the mutual quantity of the brand to be analyzed on each platform through the following formula1：
Y1＝100+(X1-AVERAGE1)/(MAX1–MIN1)*100；
Multiplying a preset first platform weighting coefficient of each platform with corresponding index information of the mutual amount, and accumulating to obtain the index information of the mutual amount of the brand to be analyzed;
wherein, X is1The interaction quantity value of the brand to be analyzed on the platform is obtained; the AVERAGE1The average value of the interaction quantity values of two or more brands in the platform is obtained; the MAX1The maximum value of the interaction quantity value in two or more brands in the platform; the MIN1Is the minimum value of the mutual quantity value in two or more brands in the platform.
4. The method according to claim 2, wherein when the brand related information includes volume of sound, the converting each brand related information of the brand to be analyzed into corresponding index information includes:
calculating the index information Y of the sound volume of the brand to be analyzed on each platform through the following formula2：
Y2＝100+(X2-AVERAGE2)/(MAX2–MIN2)*100；
Multiplying a preset second platform weighting coefficient by corresponding acoustic quantity index information, and accumulating to obtain acoustic quantity index information of the brand to be analyzed;
wherein, X is2The sound volume value of the brand to be analyzed on the platform; the AVERAGE2The average value of the sound volume values of two or more brands in the platform is obtained; the MAX2The maximum value of the sound volume numerical value in two or more brands in the platform; the MIN2Is the minimum value of the sound volume values in two or more brands in the platform.
5. The method of claim 2, wherein when the brand-related information includes positive and negative emotion data, the converting each brand-related information of the brand to be analyzed into corresponding index information comprises:
counting the positive and negative emotion surface data to obtain positive and negative emotion surface post statistical information;
calculating index information corresponding to positive and negative emotion data according to the obtained statistical information of positive and negative emotion posts:
(number of posts with all platforms containing positive emotion words-number of posts with all platforms containing negative emotion words)/(number of posts with all platforms containing positive emotion words + number of posts with all platforms containing negative emotion words) × 100;
(the number of posts of all platform emotion positive words + the number of posts of all platforms which do not contain emotion positive and negative words)/the total number of posts contained in all platform emotion positive and negative data is 100;
the total number of posts of all platforms containing the positive emotion words/the total number of posts contained in the positive emotion face data and the negative emotion face data of all platforms is 100;
calculating index information Y of the emotion positive and negative surface data of the brand to be analyzed on each platform through the following formula3：Y3＝100+(X3-AVERAGE3)/(MAX3–MIN3) 100, x; multiplying a preset third platform weighting coefficient by index information of corresponding emotion positive and negative surface data, and accumulating to obtain the index information of the sound volume of the brand to be analyzed;
wherein the positive and negative emotion post statistics comprise one or any combination of the following: number of posts and post of all platforms containing emotional positive wordsThe number of posts of which the platforms contain negative emotion words, the number of posts of which all platforms do not contain positive emotion words and negative emotion words, the total number of posts contained in positive emotion data and negative emotion data of all platforms, the number of posts of which each platform contains positive emotion words and the number of posts of which each platform contains negative emotion words; said X3Scoring the positive and negative emotion surfaces of the brand to be analyzed on the current platform; the AVERAGE3The average value of the emotion positive and negative scores of two or more brands in the current platform is obtained; the MAX3The maximum value of the emotion positive and negative surface scores in two or more brands in the current platform is obtained; the MIN3The minimum value of the positive and negative scores of the emotion in two or more brands in the current platform is obtained; the positive and negative emotion scores comprise scores obtained by the following formula: (number of posts the current platform contains positive emotion words-number of posts the current platform contains negative emotion words)/(number of posts the current platform contains positive emotion words + number of posts the current platform contains negative emotion words) × 100.
6. The method according to any one of claims 1 to 5, wherein after obtaining brand related information of the brand to be analyzed, the method further comprises:
and performing dewatering treatment on the acquired information related to the brand.
7. A computer storage medium having a computer program stored thereon, which, when being executed by a processor, implements a method of implementing brand analysis as claimed in any one of claims 1 to 6.
8. A terminal, comprising: a memory and a processor, the memory having a computer program stored therein; wherein the content of the first and second substances,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of implementing brand analysis as recited in any of claims 1-6.
9. An apparatus for implementing brand analysis, comprising: an acquisition unit and a determination unit; wherein the content of the first and second substances,
the acquisition unit is used for: obtaining brand related information of a brand to be analyzed from social public opinion data;
the determination unit is used for: determining the fondness information of the brand to be analyzed according to the acquired related information of the brand;
wherein the brand related information comprises information of one or any combination of the following brands: volume, amount of interaction, and positive and negative emotion data.
10. The apparatus according to claim 9, wherein the determining unit is specifically configured to:
converting each brand related information of the brand to be analyzed into corresponding index information;
and multiplying a preset index weighting coefficient by each corresponding index information, and accumulating to obtain the preference information.
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