CN112651228A - Method for identifying crowdsourcing design effective participants in internet technology community - Google Patents
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Abstract
The invention relates to the technical field of internet technology, in particular to a method for identifying crowdsourcing design effective participants in an internet technology community, which can eliminate useless information, accurately screen effective users with design innovation capacity, recruit high-quality design participants and simultaneously have a perfect evaluation index system for the crowdsourcing design effective participants; the method comprises the following steps: s1, acquiring contribution degree information of technical community users; s2, acquiring each article issued by the user and corresponding evaluation parameters according to the technical community user information; s3, designing relevance according to article content statistics issued by a user; s4, calculating the weight values of the user contribution degree information, the article evaluation parameters and the article content design relevance through a coefficient of variation method; and S5, counting the characteristic value of each user according to the contribution degree information of each user, the article evaluation parameters and the relevance degree of the comparison sequence of article content design relevance and the reference sequence.
Description
Technical Field
The invention relates to the technical field of internet technology, in particular to a method for identifying crowdsourcing design effective participants in an internet technology community.
Background
Online crowdsourcing is a new business model that is created in 2006 and aims to create economic value by distributing complex work to the public through the internet in a collaborative manner after the complex work is disassembled. The crowdsourcing design mode is a method of subpackaging part or all of design work to organizations or individuals with corresponding capabilities and resources through an internet platform, and factors such as the scale of the overall design work, a task decomposition mode, capability requirements, participating crowd categories/roles, participant management and motivation, a task package sending mode, acceptance criteria/modes, cost and the like need to be comprehensively considered. The premise for implementing the crowdsourcing design is to locate and recruit user individuals with design-related capabilities, and the internet of the individuals is aggregated by various technical communities such as station cool, CSDN forum, Chinese mechanical community, UI China and the like.
In recent years, more and more enterprises begin to conduct product development activities by means of a crowdsourcing design mode to cope with the trend of increasingly diversified market demands, however, in the concrete implementation process of the mode, the inventor finds that at least the following problems exist in the prior art:
(1) professional crowdsourcing design service platforms operated by enterprises/third parties are usually low in popularity and weak in public influence, and design participants with sufficient quality are difficult to recruit;
(2) the internet technology community comprises a large number of invalid users such as advertisement publishers and water filling persons, and crowdsourcing design activity organizers lack strategies and methods capable of accurately identifying valid users with design innovation capacity;
(3) there is a lack of an evaluation index system for the active participants of crowd-sourced designs.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for identifying crowdsourcing design effective participants in an internet technology community, which can eliminate useless information, accurately identify effective users with design innovation capacity, recruit high-quality design participants and simultaneously has a perfect evaluation index system for the crowdsourcing design effective participants.
The invention discloses a method for identifying crowdsourcing design effective participants in an internet technology community, which comprises the following steps of:
s1, acquiring contribution degree information of technical community users;
s2, acquiring each article issued by the user and corresponding evaluation parameters according to the technical community user information;
s3, designing relevance according to article content statistics issued by a user;
s4, calculating the weight values of the user contribution degree information, the article evaluation parameters and the article content design relevance through a coefficient of variation method;
s5, according to the contribution degree information of each user, the article evaluation parameters and the relevance degree of the comparison sequence of article content design relevance and the reference sequence, counting the characteristic value of each user;
and S6, selecting the users with the characteristic values exceeding the preset relevance threshold value as the effective participants of the crowd-sourced design.
In the method for identifying crowdsourced design effective participants in the internet technology community, in the step S4, the user points, the post forwarding number, the post comment number, the product structure/function/appearance related words in the text content contributed by the user, the technology related words, the design related words, the effective length of the contributed content, and the contribution content timeliness are used as the indexes for evaluating the effectiveness of the participants, and the importance weight of each evaluation index is calculated by using a coefficient of variation method.
The invention discloses a method for identifying crowdsourcing design effective participants in an internet technology community, which comprises the following steps of:
the user integral, the post forwarding number and the post comment number are statistical data directly taken from an internet technology community;
"product structure/function/appearance related vocabulary in user-contributed text content", "technology related vocabulary", "design related vocabulary" are the number of corresponding vocabulary appearing in the article issued by the user;
"effective length of contribution content":
wherein N isa、Nb、Nc、NdRespectively representing the vocabulary number, the product structure/function/appearance related vocabulary number, the technology related vocabulary number and the design related vocabulary number in the article issued by the user;
"contribution content timeliness": an article published within the last two months is denoted 2 and one published two months ago is denoted 1.
The invention discloses a method for identifying crowdsourcing design effective participants in an internet technology community, which comprises the following steps of:
wherein i is 1,2, …, n; viIs the coefficient of variation of the i index, i.e. the coefficient of standard deviation; sigmaiIs the standard deviation of the i index;
is the average of the i index.
The invention discloses a method for identifying crowdsourcing design effective participants in an internet technology community, which comprises the following steps of:
the invention discloses a method for identifying crowdsourcing design effective participants in an internet technology community.
According to the method for identifying the active participants of the crowdsourcing design in the Internet technology community, the threshold value can be modified according to the requirements of the crowdsourcing design.
Compared with the prior art, the invention has the beneficial effects that: useless information can be eliminated, effective users with design innovation capability can be accurately screened, high-quality design participants are recruited, and meanwhile, the evaluation index system for crowdsourcing design effective participants is complete.
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FIG. 1 is a logic flow diagram of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
The method comprises the steps of obtaining grade information of technical community users through a data mining technology (the invention is not embodied), wherein the grade information comprises points, contribution values, grades and the like, contribution contents such as postings, postbacks and other texts, and comment numbers, forwarding numbers and the like below the postings; the method comprises the following steps of taking user points, post forwarding numbers, post comment numbers, product structure/function/appearance related words in text contents contributed by users, technology related words, design related words, effective length of contribution contents and contribution content timeliness as indexes for evaluating the effectiveness of participants, wherein the statistical calculation method of each index comprises the following steps:
the user integral, the post forwarding number and the post comment number are statistical data directly taken from an internet technology community;
"product structure/function/appearance related vocabulary in user-contributed text content", "technology related vocabulary", "design related vocabulary" are the number of corresponding vocabulary appearing in the article issued by the user;
"effective length of contribution content":
wherein N isa、Nb、Nc、NdRespectively representing the vocabulary number, the product structure/function/appearance related vocabulary number, the technology related vocabulary number and the design related vocabulary number in the article issued by the user;
"contribution content timeliness": an article published within the last two months is denoted 2 and one published two months ago is denoted 1.
Calculating the importance weight of each evaluation index by using a coefficient of variation method, and the method comprises the following steps:
1) the coefficient of variation formula of each index is as follows:
in the formula ViIs the coefficient of variation of the i-th index, also known as the coefficient of standard deviation; sigmaiIs the standard deviation of the i index;
is the average of the i index.
2) The weight of each index is as follows:
selecting the optimal values of all indexes in the research sample to form a reference sequence; and calculating the association degree between the candidate user index sequence and the reference sequence by utilizing gray association analysis, wherein the gray association analysis calculation is specifically as follows:
step 1, carrying out dimensionless processing on original data:
Xk(i) and y (i) respectively represent comparison sequences and reference sequences, k is 1,2, …, m, i is 1,2, …, n, m represents the number of users to be sorted, and n represents the number of indexes; the original data is normalized by using an averaging method, and the formula is as follows:
in the formula: x is the number ofkiThe quantized value of the ith index of the kth target user; x is the number ofiThe average value of the ith index in the user set to be ranked is obtained; y isiIs the quantized value of the ith index in the reference sequence; it should be noted that, in the subsequent calculation process, some users whose index values are the same as the corresponding index values in the reference sequence need to be removed from the data normalized by the averaging method, so as to avoid generating invalid results;
step 2, calculating a grey correlation coefficient;
the calculation formula of the gray correlation coefficient is as follows:
in the formula:
Δ3＝|Y'(i)-X'k(i) i, where M ═ 1, 2.., M }, N ═ 1, 2.., N }; zeta is the resolution factor at [0,1 ]]The interval value is usually 0.5 ζ;
step 3, calculating grey correlation;
the grey correlation is calculated by adopting a weighting method, and the formula is as follows:
in the formula: w is aiIs an index weighted value; sorting according to the relevance of each user to obtain user validity sorting; the relevance value is higher than a preset threshold value, namely crowdsourcingCounting the active participants.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (7)
1. A method for identifying crowdsourced design active participants in an Internet technology community is characterized by comprising the following steps:
s1, acquiring contribution degree information of technical community users;
s2, acquiring each article issued by the user and corresponding evaluation parameters according to the technical community user information;
s3, designing relevance according to article content statistics issued by a user;
s4, calculating the weight values of the user contribution degree information, the article evaluation parameters and the article content design relevance through a coefficient of variation method;
s5, according to the contribution degree information of each user, the article evaluation parameters and the relevance degree of the comparison sequence of article content design relevance and the reference sequence, counting the characteristic value of each user;
and S6, selecting the users with the characteristic values exceeding the preset relevance threshold value as the effective participants of the crowd-sourced design.
2. The method as claimed in claim 1, wherein in S4, the "user score", "post forwarding number", "post comment number", "product structure/function/appearance related vocabulary in text content contributed by user", "technology related vocabulary", "design related vocabulary", "effective length of contribution content", "contribution content timeliness" are used as indicators for evaluating the effectiveness of participants, and the importance weight of each evaluation indicator is calculated by using a coefficient of variation method.
3. The method of claim 2, wherein the statistical calculation of the metrics comprises:
the user integral, the post forwarding number and the post comment number are statistical data directly taken from an internet technology community;
"product structure/function/appearance related vocabulary in user-contributed text content", "technology related vocabulary", "design related vocabulary" are the number of corresponding vocabulary appearing in the article issued by the user;
"effective length of contribution content":
wherein N isa、Nb、Nc、NdRespectively representing the vocabulary number, the product structure/function/appearance related vocabulary number, the technology related vocabulary number and the design related vocabulary number in the article issued by the user;
"contribution content timeliness": an article published within the last two months is denoted 2 and one published two months ago is denoted 1.
4. The method of claim 3, wherein the coefficient of variation formula of each index is as follows:
wherein i is 1,2, …, n; viIs the coefficient of variation of the i index, i.e. the coefficient of standard deviation; sigmaiIs the standard deviation of the i index;
is the average of the i index.
5. The method of claim 4, wherein the weight of each index is calculated by the formula:
6. the method as claimed in claim 5, wherein the method selects the optimal value of each index in the research sample to form a reference sequence, and calculates the association degree between the candidate user index sequence and the reference sequence by using gray association analysis, and if the association degree is higher than a preset threshold value, it is the valid participant of the crowd-sourced design.
7. The method of claim 1, wherein the threshold is modified according to requirements of a crowdsourcing design.
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Patent Citations (4)
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| CN103810169A (en) * | 2012-11-06 | 2014-05-21 | 腾讯科技（深圳）有限公司 | Method and device for detecting community domain experts |
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| CN109886581A (en) * | 2019-02-25 | 2019-06-14 | 天津工业大学 | Participant's selection method based on the quality of data in a kind of mobile gunz perception task |
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