CN108268618A - A kind of microblogging temperature analyzes acquisition methods - Google Patents
A kind of microblogging temperature analyzes acquisition methods Download PDFInfo
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Abstract
The present invention relates to a kind of microblogging temperatures to analyze acquisition methods, is primarily based on each primary data information (pdi) specified corresponding to Twitter message, obtains corresponding each microblogging factor data；Then the corresponding coefficient of each microblogging factor data difference is obtained；Then it is operated for each microblogging factor data dimensionality reduction, obtains the weight of corresponding each micro-blog information dimension and each micro-blog information dimension, and then obtain the data of each micro-blog information dimension；Finally obtain microblogging temperature index；It is so designed that, microblogging temperature index is not only judged in terms of previous propagation, the influence of microblogging content itself and the influence of bloger's characteristic are further comprised, " microblog water army " filter algorithm is more added to and microblogging plays an active part in the influence of number of users, can more fully embody the true temperature of microblogging.
Description
Technical field
The present invention relates to a kind of microblogging temperatures to analyze acquisition methods, belongs to social networks technical field.
Background technology
Current microblogging has become one of important medium of network social intercourse, in the side such as knowledge dissemination, Information Sharing, Social Public Feelings
Face affects the behavior of people.The abbreviation of microblogging, that is, miniature blog, that is to say one kind of blog, be one kind by concern machine
System shares the social network-i i-platform of the broadcast type of brief real time information.Microblogging is one based on customer relationship Information Sharing, propagation
And the platform obtained.User can set up personal community by the various clients such as WEB, WAP, (be accorded with 140 words including punctuate
Number) word fresh information, and realize share immediately.The concern mechanism of microblogging be divided into can unidirectionally, can be two kinds two-way.Microblogging conduct
One kind shares and intercommunion platform, more focuses on timeliness and randomness.Microblogging can more give expression to thought all the time and newest
Dynamically, and blog is then more heavily weighted toward and combs oneself finding whithin a period of time, what is heard, felt.Therefore, microblogging is current social activity
Important way in network, and microblogging temperature is an index of the Twitter message of evaluation, in current techniques, there are no a accurate
Mode realize the evaluation of microblogging temperature, therefore the prior art is accurate not enough for the evaluation of microblogging.
Invention content
The technical problems to be solved by the invention are to provide a kind of microblogging that can be directed to Twitter message realization accurate evaluation
Temperature analyzes acquisition methods.
In order to solve the above-mentioned technical problem the present invention uses following technical scheme：The present invention devises a kind of microblogging temperature point
Acquisition methods are analysed, the acquisition of target Twitter message temperature is used to implement, includes the following steps：
Step A. obtains each primary data information (pdi) specified corresponding to target Twitter message, and for each initial data
Information is handled, and corresponding each microblogging factor data is obtained, subsequently into step B；
Step B. is directed to each microblogging factor data, obtains the corresponding coefficient of each microblogging factor data difference, then
Enter step C；
Step C. is directed to each microblogging factor data, carries out factorial analysis, and dimensionality reduction operates, obtains corresponding each micro-
The weight of rich information dimension and each micro-blog information dimension, subsequently into step D；
Step D. based on each microblogging factor data corresponding coefficient respectively, according to each micro-blog information dimension with it is each
Correspondence between microblogging factor data by method of weighting, obtains the data of each micro-blog information dimension, subsequently into step
Rapid E；
Step E. is according to the weight of each micro-blog information dimension and the data of each micro-blog information dimension, by following public affairs
Formula：
Microblogging temperature index F is obtained, wherein, I represents the number of micro-blog information dimension, αiRepresent i-th of micro-blog information dimension
The weight of degree, FiRepresent the data of i-th of micro-blog information dimension.
As a preferred technical solution of the present invention：In the step B, for each microblogging factor data, by adopting
With factor extraction and factor rotation method, the corresponding coefficient of each microblogging factor data difference is obtained.
As a preferred technical solution of the present invention：In the step C, for each microblogging factor data, led
Components Factor is analyzed, and dimensionality reduction operates.
As a preferred technical solution of the present invention：It is each corresponding to target Twitter message to specify in the step A
Primary data information (pdi), including amount of reading, thumb up number, comment number, forwarding number, bloger's bean vermicelli number, enliven number of days, microblogging word number,
Picture number propagates duration.
As a preferred technical solution of the present invention：In the step A, for each primary data information (pdi) by following step
Suddenly it is handled, obtains corresponding each microblogging factor data；
Step A1. is forwarded according to the forwarding number with effective word forwarding content and is commented on number, and commented according to participation
By or forwarding user the hair amount of winning less than 3, and the bean vermicelli number of user is considered as corpse user, acquisition corpse user less than 5
It counts and the original rate of user's Fa Bo contents is considered as waterborne troops user for 0, waterborne troops's number of users is obtained, subsequently into step A2；
Step A2. obtains word circularity according to microblogging word number/140；According to picture number/9, picture circularity is obtained；
According to forwarding and commenting on number/amount of reading, depth spreading rate is obtained；According to the sum of corpse number of users, waterborne troops's number of users and amount of reading
Ratio, negative spreading rate is obtained, subsequently into step A3；
Step A3. by bloger's bean vermicelli number, enliven number of days, word circularity, picture circularity, propagate duration, depth propagate
Rate, negative spreading rate are as each microblogging factor data.
A kind of microblogging temperature analysis acquisition methods of the present invention compared with prior art, are had using above technical scheme
Following technique effect：The microblogging temperature analysis acquisition methods that the present invention designs, the network data based on microblogging, analysis information is micro-
Propagation characteristic in rich sends out rich client distribution, microblogging propagation time and microblogging including microblogging and propagates the propagation characteristics such as participation,
Refining influences the various factors that microblogging is propagated；And the fingers such as user characteristics, content characteristic and characteristics in spreading information based on microblogging
Mark, the temperature evaluation model based on factor analysis improved are measured by the various data characteristicses to single microblogging
And statistics, and usage factor analysis carries out finishing analysis to data, and finally its result is ranked up and compared, analysis is arranged with former
The difference producing cause of sequence, the results showed that this model has high accuracy, and the method for the present invention passes simultaneously in view of negative
It broadcasts and propagates the phenomenon that both are common and very important in microblogging with depth, can more integrate the temperature for embodying microblogging.
Description of the drawings
Fig. 1 is the flow diagram of microblogging temperature analysis acquisition methods designed by the present invention；
Fig. 2 is factorial analysis rubble figure in Application Example of the present invention；
Fig. 3 is the component-part diagram of revolution space in Application Example of the present invention；
Fig. 4 is that data delete the analysis chart after choosing arranges in Application Example of the present invention.
Specific embodiment
The specific embodiment of the present invention is described in further detail with reference to the accompanying drawings of the specification.
As shown in Figure 1, the present invention devises a kind of microblogging temperature analysis acquisition methods, it is used to implement target Twitter message heat
The acquisition of degree in actual application, specifically comprises the following steps：
Step A. obtains each primary data information (pdi) specified corresponding to target Twitter message, and for each initial data
Information is handled, and corresponding each microblogging factor data is obtained, subsequently into step B.
In practical application, for the primary data information (pdi) specified each corresponding to target Twitter message, specific design includes
Amount of reading thumbs up number, comment number, forwarding number, bloger's bean vermicelli number, enlivens number of days, microblogging word number, picture number, propagates duration.
It based on above-mentioned nine primary data information (pdi)s, is handled, is obtained as follows for each primary data information (pdi)
Corresponding each microblogging factor data；
Step A1. is forwarded according to the forwarding number with effective word forwarding content and is commented on number, and commented according to participation
By or forwarding user the hair amount of winning less than 3, and the bean vermicelli number of user is considered as corpse user, acquisition corpse user less than 5
It counts and the original rate of user's Fa Bo contents is considered as waterborne troops user for 0, waterborne troops's number of users is obtained, subsequently into step A2.
Step A2. obtains word circularity according to microblogging word number/140；According to picture number/9, picture circularity is obtained；
According to forwarding and commenting on number/amount of reading, depth spreading rate is obtained；According to the sum of corpse number of users, waterborne troops's number of users and amount of reading
Ratio, negative spreading rate is obtained, subsequently into step A3.
Step A3. by bloger's bean vermicelli number, enliven number of days, word circularity, picture circularity, propagate duration, depth propagate
Rate, negative spreading rate are as each microblogging factor data.
Step B. uses SPPS softwares, for each microblogging factor data, is extracted and factor rotation side by using the factor
Method obtains the corresponding coefficient of each microblogging factor data difference, subsequently into step C.
Step C. is directed to each microblogging factor data, using SPPS softwares, carries out Principal Component Factor Analysis, and dimensionality reduction is grasped
Make, the weight of corresponding each micro-blog information dimension and each micro-blog information dimension is obtained, subsequently into step D.
Step D. based on each microblogging factor data corresponding coefficient respectively, according to each micro-blog information dimension with it is each
Correspondence between microblogging factor data by method of weighting, obtains the data of each micro-blog information dimension, subsequently into step
Rapid E.
Step E. is according to the weight of each micro-blog information dimension and the data of each micro-blog information dimension, by following public affairs
Formula：
Microblogging temperature index F is obtained, wherein, I represents the number of micro-blog information dimension, αiRepresent i-th of micro-blog information dimension
The weight of degree, FiRepresent the data of i-th of micro-blog information dimension.
By above-mentioned designed microblogging temperature analysis acquisition methods, it is applied in reality, from April 18th, 2017, Sina was micro-
Rich platform has chosen ten microbloggings in its hot topic push in order, designed according to this invention by the data of this ten microbloggings
Microblogging temperature analysis acquisition methods handled.Specifically comprise the following steps：
Step A. respectively for ten Twitter messages, obtain the amount of reading corresponding to Twitter message, thumb up number, comment number,
Forwarding number, bloger's bean vermicelli number enliven number of days, microblogging word number, picture number, propagate duration, and for this nine original numbers it is believed that
Breath is handled as follows, and the corresponding each microblogging factor data of acquisition, i.e. bloger's bean vermicelli number enliven number of days, word
Circularity, propagates duration, depth spreading rate, negative spreading rate at picture circularity, and then obtains each Twitter message difference respectively
Corresponding each microblogging factor data, it is as shown in table 1 below, subsequently into step B.
Step A1. is forwarded according to the forwarding number with effective word forwarding content and is commented on number, and commented according to participation
By or forwarding user the hair amount of winning less than 3, and the bean vermicelli number of user is considered as corpse user, acquisition corpse user less than 5
It counts and the original rate of user's Fa Bo contents is considered as waterborne troops user for 0, waterborne troops's number of users is obtained, subsequently into step A2.
Step A2. obtains word circularity according to microblogging word number/140；According to picture number/9, picture circularity is obtained；
According to forwarding and commenting on number/amount of reading, depth spreading rate is obtained；According to the sum of corpse number of users, waterborne troops's number of users and amount of reading
Ratio, negative spreading rate is obtained, subsequently into step A3.
Step A3. is by bloger's bean vermicelli number x1, enliven number of days x2, word circularity x3, picture circularity x4, propagate duration x5、
Depth spreading rate x6, negative spreading rate x7As each microblogging factor data.
Table 1
Step B. is respectively for ten Twitter messages, using SPPS softwares, for Twitter message each microblogging because of subnumber
According to, by using the factor extract with factor rotation method, obtain each microblogging factor data corresponding coefficient respectively, such as following table
Shown in 2, subsequently into step C.Wherein, factor rotation method is the rotary process standardized with Kaiser.
Table 2
Carrying out factorial analysis has precondition, before factorial analysis is carried out, first to carry out KMO's and Bartlett
It examines.KMO statistics：It is by comparing the size of simple correlation coefficient and partial correlation coefficient between each variable, between judgment variable
Correlation, when correlation is strong, partial correlation coefficient is much smaller than simple correlation coefficient, and KMO values are close to 1.Under normal circumstances, KMO>0.9
It is very suitable for factorial analysis；0.8 ＜ KMO ＜ 0.9 are suitble to；More than 0.7 still, and poor effect when 0.6, less than 0.5 is not suitable for making
Factorial analysis.Following extraction factor, according to characteristic value be more than 1 and information interpretation percentage be more than 80% be standard, Yi Gongti
3 common factors have been taken, can be further discovered that 3 common factors can explain the 30.637% of temperature relevant information respectively,
28.938% and 21.542%.Finally add up to explain the 81.117% of overall information this ratio, this result is shown
3 common factors can be good at the overall information for reflecting microblogging temperature.Further according to the feedback component matrix pair of factorial analysis
Each common factor meaning and its composition are analyzed.Following information can be summed up：First common factor and word Full Ratio and figure
Piece Full Ratio has very high correlativity；It second common factor and bean vermicelli number and enlivens number of days and has very high correlativity；Third public affairs because
Son propagates duration, severe spreading rate and negatively propagation rate dependence is stronger, that is, performs following steps C.
Step C. is directed to ten Twitter messages respectively, for above-mentioned seven microblogging factor datas VAR00001 extremely
VAR00007 using SPPS softwares, carries out Principal Component Factor Analysis, and dimensionality reduction operates, as shown in the following table 3 and table 4.It obtains opposite
The three micro-blog information dimension F answered1、F2、F3And the weight α of each micro-blog information dimension1、α2、α3, subsequently into step D.
Wherein, rubble figure is as shown in Fig. 2, the component-part diagram of revolution space is as shown in Figure 3.Wherein, the first micro-blog information dimension F1, it is microblogging
Content information, including word circularity, picture circularity；Second micro-blog information dimension F2, it is microblogging bloger's information, including bloger
Bean vermicelli number enlivens number of days；Third micro-blog information dimension F3, information is propagated for microblogging, including propagating duration, depth spreading rate, bearing
Face spreading rate.The weight α of first micro-blog information dimension1=0.3064, the weight α of the second micro-blog information dimension2=0.2894, the
The weight α of three micro-blog information dimensions3=0.2154.
Table 3
Table 4
For ten Twitter messages, corresponding coefficient is distinguished based on each microblogging factor data respectively by step D., according to
Correspondence between each micro-blog information dimension and each microblogging factor data by method of weighting, obtains each microblogging letter
The data of dimension are ceased, it is as follows：
First micro-blog information dimension F1=0.399x3-0.485x4；
Second micro-blog information dimension F2=0.460x1+0.474x2；
Third micro-blog information dimension F3=0.498x5+0.448x6+0.300x7；
Subsequently into step E.
Step E. for ten Twitter messages, believes respectively according to the weight of each micro-blog information dimension and each microblogging
The data of dimension are ceased, as follows：
F=(0.3064F1+0.2894F2+0.2154F3)/(0.3064+0.2894+0.2154)
Microblogging temperature index F is obtained, i.e., obtains ten Twitter message microblogging temperature index F respectively, it is as shown in table 5 below.
| The new ranking of microblogging | The original ranking of microblogging | F1 | F2 | F3 | F |
| 1 | 3 | 4341.327 | 99.70224 | -0.5257 | 1675.201 |
| 2 | 7 | 2963.807 | 30.53074 | -1.23929 | 1130.029 |
| 3 | 4 | 2770.678 | 81.9113 | -1.33651 | 1075.386 |
| 4 | 9 | 1466.657 | 8.18746 | -1.07063 | 556.6107 |
| 5 | 2 | 1110.733 | 68.36965 | -0.59919 | 443.7694 |
| 6 | 8 | 535.6219 | 12.72554 | -0.62901 | 206.6837 |
| 7 | 1 | 98.25606 | 459.8552 | -0.62814 | 201.0015 |
| 8 | 5 | 215.9245 | 59.34416 | -3.03134 | 101.9237 |
| 9 | 6 | 171.1378 | 27.64094 | -2.13985 | 73.93368 |
| 10 | 10 | 84.35302 | -13.1864 | -0.32796 | 27.06975 |
Table 5
Pass through data analysis according to ten microbloggings of the popular top news sequence interception of Sina weibo herein as can be seen from Table 5
The true temperature sequence obtained, and graphic analyses is made according to preliminary acquired mass data and microblogging type, such as Fig. 4 institutes
Show.
Embodiments of the present invention are explained in detail above in conjunction with attached drawing, but the present invention is not limited to above-mentioned implementations
Mode, within the knowledge of a person skilled in the art, can also be under the premise of present inventive concept not be departed from
It makes a variety of changes.
Claims (5)
1. a kind of microblogging temperature analyzes acquisition methods, it is used to implement the acquisition of target Twitter message temperature, which is characterized in that including
Following steps：
Step A. obtains each primary data information (pdi) specified corresponding to target Twitter message, and for each primary data information (pdi)
It is handled, corresponding each microblogging factor data is obtained, subsequently into step B；
Step B. is directed to each microblogging factor data, obtains the corresponding coefficient of each microblogging factor data difference, subsequently into
Step C；
Step C. is directed to each microblogging factor data, carries out factorial analysis, and dimensionality reduction operates, and obtains corresponding each microblogging letter
The weight of dimension and each micro-blog information dimension is ceased, subsequently into step D；
Step D. is based on the corresponding coefficient of each microblogging factor data difference, according to each micro-blog information dimension and each microblogging
Correspondence between factor data by method of weighting, obtains the data of each micro-blog information dimension, subsequently into step E；
Step E. is according to the weight of each micro-blog information dimension and the data of each micro-blog information dimension, as follows：
Microblogging temperature index F is obtained, wherein, I represents the number of micro-blog information dimension, αiRepresent the power of i-th of micro-blog information dimension
Weight, FiRepresent the data of i-th of micro-blog information dimension.
2. a kind of microblogging temperature analysis acquisition methods according to claim 1, it is characterised in that：In the step B, for each
A microblogging factor data by using factor extraction and factor rotation method, is obtained corresponding to each microblogging factor data difference
Coefficient.
3. a kind of microblogging temperature analysis acquisition methods according to claim 1, it is characterised in that：In the step C, for each
A microblogging factor data carries out Principal Component Factor Analysis, and dimensionality reduction operates.
4. a kind of microblogging temperature analysis acquisition methods according to claim 1, it is characterised in that：In the step A, target is micro-
Each primary data information (pdi) specified corresponding to rich message including amount of reading, thumbs up number, comment number, forwarding number, bloger's bean vermicelli
Number enlivens number of days, microblogging word number, picture number, propagates duration.
5. a kind of microblogging temperature analysis acquisition methods according to claim 4, it is characterised in that：In the step A, for each
A primary data information (pdi) is handled as follows, obtains corresponding each microblogging factor data；
Step A1. according to effective word forwarding content forwarding number, forward and comments on number, and according to participation comment on or
The hair amount of winning of the user of forwarding is less than 3, and the bean vermicelli number of user is considered as corpse user less than 5, obtains corpse number of users, with
And the original rate of user's Fa Bo contents is considered as waterborne troops user for 0, waterborne troops's number of users is obtained, subsequently into step A2；
Step A2. obtains word circularity according to microblogging word number/140；According to picture number/9, picture circularity is obtained；According to
It forwards and comments on number/amount of reading, obtain depth spreading rate；According to the ratio of the sum of corpse number of users, waterborne troops's number of users and amount of reading
Value, obtains negative spreading rate, subsequently into step A3；
Step A3. by bloger's bean vermicelli number, enliven number of days, word circularity, picture circularity, propagate duration, depth spreading rate, negative
Face spreading rate is as each microblogging factor data.
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Application publication date: 20180710 |
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