CN110096650A - The analysis method and device of network connection intensity - Google Patents
The analysis method and device of network connection intensity Download PDFInfo
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Abstract
The present invention provides the analysis method and device of a kind of network connection intensity, is related to field of social network.The analysis method of the network connection intensity includes: to obtain the reply data of user；Calculate the centrad of user according to the reply data, the centrad includes: a degree centrad, intermediate centrad and close to centrad；Core-Periphery Structure model based on pre-training judges that user region, the region include: nucleus and fringe region；It calculates point degree centrad, intermediate centrad, whether be in weight of the nucleus when measuring network connection intensity close to centrad and user；According to the network connection intensity of the weight calculation user.The present invention can accurately analyze network connection intensity.
Description
Technical field
The present invention relates to field of social network, and in particular to a kind of analysis method and device of network connection intensity.
Background technique
With the rapid development of internet technology, online social networks is widely used by people, and carries out various
User mutual behavior.For example, the sharing of information resources, commenting on, thumbing up and forwarding.Network connection intensity refers to Web Community
The strength of association of middle user and other users show as the reply of topic post and the relationship being responded in social networks.
The value that network connection intensity often represents greatly the user is higher, and the quality of theme and money order receipt to be signed and returned to the sender is also relatively high.
In the prior art, network connection intensity is generally described by ATTRIBUTE INDEXs such as the quantity of posting of user, money order receipt to be signed and returned to the sender quantity, for hair
The big user of note quantity, money order receipt to be signed and returned to the sender quantity, network connection intensity are also big.
However, the inventor of the present application discovered that above-mentioned analysis method is in use, rely only on the information analyses such as quantity of posting
Network connection intensity is too absolute, can not accurately analyze network connection intensity.
Summary of the invention
(1) the technical issues of solving
In view of the deficiencies of the prior art, the present invention provides a kind of analysis method of network connection intensity and devices, solve
The problem of prior art can not accurately analyze network connection intensity.
(2) technical solution
In order to achieve the above object, the present invention is achieved by the following technical programs:
The present invention solves a kind of analysis method of network connection intensity provided by its technical problem, comprising the following steps:
Obtain the reply data of user；
The centrad of user is calculated according to the reply data, the centrad includes: a degree centrad, intermediate centrad
With close to centrad；
Core-Periphery Structure model based on pre-training judges user region, the region include: nucleus and
Fringe region；
It calculates described degree centrad, the intermediate centrad, described whether be in core space close to centrad and user
Weight of the domain when measuring network connection intensity；
According to the network connection intensity of the weight calculation user.
Preferably, measurement index when described degree centrad calculates includes: corresponding point out-degree and corresponding point in-degree；It is described
Measurement index when intermediate centrad calculates includes: relatively intermediate centrad；The measurement index when calculating close to centrad
It include: in-degree close to centrad, out-degree close to centrad.
Preferably, the calculation method of described degree centrad are as follows:
The number for being pointing directly at the other users of user is obtained, corresponding point in-degree is obtained；
The number for the other users that user is pointing directly at is obtained, corresponding point out-degree is obtained；
Point degree centrad is obtained based on the corresponding point in-degree and the corresponding point out-degree.
Preferably, the calculation method of the intermediate centrad are as follows:
It obtains user and appears in the number in the most short internuncial pathway of any two other users, obtain relatively intermediate center
Degree；
Intermediate centrad is obtained based on the relatively intermediate centrad.
Preferably, the calculation method close to centrad are as follows:
The shortest path sum of the distance that each other users are pointing directly at user is obtained, obtains in-degree close to centrad；
The shortest path sum of the distance that user is pointing directly at each other users is obtained, obtains out-degree close to centrad；
It is obtained close to centrad and the out-degree close to centrad close to centrad based on the in-degree.
Preferably, the calculation method of the network connection intensity of the user includes:
Corresponding point out-degree, corresponding point in-degree, relatively intermediate centrad, in-degree are calculated close to centrad, out-degree close to center
Whether user is in the weight of nucleus in degree and Core-periphery Model；
Network connection intensity, calculation formula are calculated according to the index weights are as follows:
Wherein:
XiIndicate the network connection intensity of i-th of user；
xijIndicate the jth item index of i-th of user；
wiIndicate weight of each index relative to overall performane, i.e.,
Preferably, the method for calculating weight includes: entropy assessment.
The present invention solves a kind of analytical equipment of network connection intensity provided by its technical problem, which is characterized in that packet
It includes:
Data acquisition module, for obtaining the reply data of user；
Centrad module, for calculating the centrad of user according to the reply data, the centrad includes: in a degree
Heart degree, intermediate centrad and close to centrad；
User area judgment module judges user region, institute for the Core-Periphery Structure model based on pre-training
Stating region includes: nucleus and fringe region；
Network connection intensity computing module, for calculating point degree centrad, intermediate centrad, being close to centrad and user
The no weight for being in nucleus when measuring network connection intensity；According to the network connection intensity of the weight calculation user.
Preferably, in the centrad module, the measurement index of described degree centrad includes: corresponding point out-degree and opposite
Point in-degree；The measurement index of the intermediate centrad includes: relatively intermediate centrad；The measurement index packet close to centrad
Include: in-degree is close to centrad, out-degree close to centrad.
Preferably, in the network connection intensity computing module, the calculation method packet of the network connection intensity of the user
It includes:
Corresponding point out-degree, corresponding point in-degree, relatively intermediate centrad, in-degree are calculated close to centrad, out-degree close to center
Degree and Core-periphery Model in user whether nucleus index weights；
Network connection intensity, calculation formula are calculated according to the index weights are as follows:
Wherein:
XiIndicate the network connection intensity of i-th of user；
xijIndicate the jth item index of i-th of user；
wiIndicate weight of each index relative to overall performane, i.e.,
(3) beneficial effect
The present invention provides a kind of analysis method of network connection intensity and devices.Compared with prior art, have following
The utility model has the advantages that
The present invention calculates the centrad of user for the reply data of user, wherein centrad includes following several types:
Point degree centrad, intermediate centrad and close to centrad；The Core-Periphery Structure model based on pre-training judges user institute simultaneously
In region, including nucleus and fringe region；Calculate point degree centrad, centre centrad, close to centrad and user whether
It is in weight of the nucleus when measuring network connection intensity；According to the network connection intensity of weight calculation user, therefore this
Invention can be from the network connection intensity of two angle analysis users of centrad attribute and user region of user, and obtains
Specific calculated value can accurately analyze network connection intensity.Meanwhile it can be identified according to calculated network connection intensity
High-value user, enterprise or government can efficiently extract the information of high-value user, so that work is more efficient.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is the overall flow figure of network connection intensity analysis method described in the embodiment of the present invention；
Fig. 2 is the overall flow figure of network connection intensity analytical equipment described in the embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, to the technology in the embodiment of the present invention
Scheme is clearly and completely described, it is clear that and described embodiments are some of the embodiments of the present invention, rather than whole
Embodiment.Based on the embodiments of the present invention, those of ordinary skill in the art are obtained without creative efforts
The every other embodiment obtained, shall fall within the protection scope of the present invention.
The embodiment of the present application by providing the analysis method and device of a kind of network connection intensity, solve the prior art without
Method accurately analyzes network connection intensity problem, realizes the accurate analysis of network connection intensity.
Technical solution in the embodiment of the present application is in order to solve the above technical problems, general thought is as follows:
The embodiment of the present invention calculates the centrad of user for the reply data of user, wherein centrad includes following several
Seed type: point degree centrad, intermediate centrad and close to centrad；The Core-Periphery Structure model based on pre-training is sentenced simultaneously
Disconnected user region, including nucleus and fringe region；Calculate point degree centrad, centre centrad, close to centrad and
Whether user is in weight of the nucleus when measuring network connection intensity；Network connection according to weight calculation user is strong
Degree, therefore the embodiment of the present invention can be from the network of two angle analysis users of centrad attribute and user region of user
Bonding strength, and obtain specific calculated value, it can accurately analyze network connection intensity.Meanwhile being connected according to calculated network
High-value user can be identified by connecing intensity, and enterprise or government can efficiently extract the information of high-value user, so that
It works more efficient.
In order to better understand the above technical scheme, in conjunction with appended figures and specific embodiments to upper
Technical solution is stated to be described in detail.
The embodiment of the invention provides a kind of analysis methods of network connection intensity, as shown in Figure 1, comprising the following steps:
S1, the reply data for obtaining user；
S2, according to above-mentioned reply data calculate user centrad, above-mentioned centrad include: a degree centrad, centre in
Heart degree and close to centrad；
S3, the Core-Periphery Structure model based on pre-training judge that user region, the region include: core space
Domain and fringe region；
S4, it calculates above-mentioned degree centrad, above-mentioned intermediate centrad, above-mentioned whether be in core close to centrad and user
Weight of the region when measuring network connection intensity；
S5, according to the network connection intensity of above-mentioned weight calculation user.
The embodiment of the present invention calculates the centrad of user for the reply data of user, wherein centrad includes following several
Seed type: point degree centrad, intermediate centrad and close to centrad；The Core-Periphery Structure model based on pre-training is sentenced simultaneously
Disconnected user region, including nucleus and fringe region；Calculate point degree centrad, centre centrad, close to centrad and
Whether user is in weight of the nucleus when measuring network connection intensity；Network connection according to weight calculation user is strong
Degree, therefore the embodiment of the present invention can be from the network of two angle analysis users of centrad attribute and user region of user
Bonding strength, and obtain specific calculated value, it can accurately analyze network connection intensity.Meanwhile being connected according to calculated network
High-value user can be identified by connecing intensity, and enterprise or government can efficiently extract the information of high-value user, so that
It works more efficient.
Each step is described in detail below.
In step sl, the reply data of user are obtained.
For example, the embodiment of the present invention obtains April 10 days to 2018 January in 2018 from ground iron group forum-Beijing area
People's information is replied and replied to post people, topic post of all topic posts between this month on the 10, and each people that posts is corresponding
Reply data preparation come out, including topic post title, reply people's pet name, reply people and respond the attributes such as floor, partial data is such as
Shown in table 1.
1 user of table replys tables of data
In step s 2, the centrad of user is calculated according to above-mentioned reply data, above-mentioned centrad includes: a degree center
Degree, intermediate centrad and close to centrad.
Specifically, calculating, steps are as follows:
S201, point degree centrad is calculated.
Point degree centrad are as follows: in online social networks, user and other users presence are directly contacted, then during the user occupy
Cardiac status.
For measuring the index of point degree centrad in the embodiment of the present invention are as follows: corresponding point in-degree and corresponding point out-degree.
Wherein, the calculation method of corresponding point in-degree are as follows: obtain the number for being pointing directly at the other users of user, obtain opposite
Point in-degree.
Specifically, calculation formula can be with are as follows:
Wherein: CRDiIt indicates corresponding point in-degree (RD is english abbreviation, specially Relative Degree), XijIndicate point i
With the wiring quantity between point j, j is pointing directly toward the point of i, and n is the scale of network.
The calculation method of corresponding point out-degree are as follows: obtain the number for the other users that user is pointing directly at, obtain opposite point out
Degree.
Specifically, calculation formula can be with are as follows:
Wherein: CRDjIndicate corresponding point out-degree, XijIndicating the wiring quantity between point i and point j, j is the point that i is pointing directly at,
N is the scale of network.
A degree centrad is handled according to the resulting corresponding point in-degree of calculating and corresponding point out-degree, is calculated in a degree
Heart degree.
Specifically, calculation formula can be with are as follows:
Wherein: CRD(x) the opposite centrad of point x, X are indicatedijIndicate the wiring quantity between point i and point j, n is network
Scale.
Part results of measuring is as shown in table 2:
2 point degree centrad of table
As shown in Table 2, it is node 1 that it is highest, which to put out-degree, secondly numerical value 674 is node 112, node 29, node
395, the point out-degree of these nodes has been more than 300, is illustrated in forum, they often reply others' model, happy
Meaning delivers oneself view, is that the forum enlivens personage；Highest point in-degree is node 112, and numerical value reaches 986, explanation
The reply volume that the topic post that the user delivers receives is larger, causes large-scale arguement dispute.These users are likely to be the palm
The key person for having held certain information is likely to the promoter as public opinion, merits special attention.
S202, intermediate centrad is calculated.
Intermediate centrad an are as follows: if user is on a plurality of relation path simultaneously, which occupy critical role.
For measuring the index of intermediate centrad in the embodiment of the present invention are as follows: relatively intermediate centrad.
The calculation method of relatively intermediate centrad are as follows: obtain user and appear in the most short internuncial pathway of any two other users
In number, obtain relatively intermediate centrad.
Above-mentioned relatively intermediate centrad can be acquired by absolute intermediate centrad.
Specifically, calculation method can be with are as follows:
Calculate absolutely intermediate centrad, calculation formula are as follows:
Wherein: j ≠ k ≠ i, j < k；
CABiIndicate absolutely intermediate centrad (AB is english abbreviation, specially Absolute Betweenness), n is net
The scale of network, j and k are arbitrary two o'clock, b in the networkjk(i) indicate that i point is in the geodesic probability between point j and point k.
Relatively intermediate centrad, calculation formula are calculated according to absolute intermediate centrad are as follows:
Wherein: CRBi(RB is english abbreviation to the relatively intermediate centrad of expression point, represents Relative
Betweenness), CABiIndicate the absolute intermediate centrad of point, n is the scale of network.
Intermediate centrad can be indicated by relatively intermediate centrad.
Part results of measuring is as shown in table 3:
The intermediate centrad of table 3
As shown in Table 3, it is node 112 that intermediate centrad is highest, secondly numerical value 46702.902 is node 1, section
Point 46, node 39.Illustrating in the forum, many people establish connection by them, they have the ability of certain control resource,
Many information are transmitted by them.Simultaneously, the results showed that, having centrad among 152 nodes is 0, nearly 27% has been accounted for,
These people that post hardly have the ability of control resource, and the ability for transmitting information is very weak.
S203, it calculates close to centrad.
Close to centrad are as follows: the proximity degree of user and other users, the user smaller close to centrad, in network
In be more in core status.
For measuring index close to centrad in the embodiment of the present invention are as follows: in-degree is close to centrad and out-degree close to center
Degree.
Wherein, calculation method of the in-degree close to centrad are as follows: obtain the shortest path that each other users are pointing directly at user
Diameter sum of the distance obtains in-degree close to centrad.
Specifically, in-degree can be indicated with opposite in-degree close to centrad close to centrad.
Calculation method can be with are as follows:
Absolute in-degree is calculated first close to centrad, calculation formula are as follows:
Wherein:Indicate absolute in-degree close to centrad, dijIndicate that (point j is directed toward the geodetic between point i) by point i and point j
Linear distance.
Opposite in-degree is calculated close to centrad, calculation formula close to centrad according to absolute in-degree are as follows:
Wherein:Be point opposite in-degree close to centrad,Be point absolute in-degree close to centrad, n is net
Network scale.
Calculation method of the out-degree close to centrad are as follows: obtain the shortest path distance that user is pointing directly at each other users
The sum of, out-degree is obtained close to centrad.
Specifically, out-degree can be indicated with opposite out-degree close to centrad close to centrad.
Calculation method can be with are as follows:
Absolute out-degree is calculated first close to centrad, calculation formula are as follows:
Wherein:Indicate absolute out-degree close to centrad, dijIt is point j and the point i (geodesic curve between point j direction point i)
Distance.
According to absolute out-degree close to centrad, opposite out-degree is calculated close to centrad, calculation formula are as follows:
Wherein:Indicate opposite out-degree close to centrad,Absolute out-degree is indicated close to centrad, n is network rule
Mould.
It can be indicated close to centrad by in-degree close to centrad and out-degree close to centrad.
Part results of measuring is as shown in table 4:
Table 4 is close to centrad
As shown in Table 4, the in-degree of node 338 illustrates that the node can arrive at it with the smallest path close to centrad minimum
He is member, according to the table 6 in being ranked up from high to low close to centrad, close to centrad highest, locates in a network
In the status for comparing core, the ability not controlled by other members is higher.In forum member, the small member of nodal distance index
It should draw attention, these members are relatively more active during information is transmitted, and information can be communicated to net with shortest path
Other members in network.
In step s3, the Core-Periphery Structure model based on pre-training judges user region, above-mentioned zone packet
It includes: nucleus and fringe region.
One edge structural model of core is gone according to the tightness degree contacted between user in network by the user in network point
For two regions: nucleus and fringe region.User positioned at nucleus has important status, net in a network
Network bonding strength is also bigger.
There are three aspect features in structure for the ideal model of core-edge: 1, two pairwise correlation of core member；2, core
There are relationships between member and certain edge members；3, relationship is not present between edge member.
The embodiment of the present invention carries out many experiments in pre-training model, by data grouping, measures every group of data and ideal
The degree of closeness of model, to find out the Core-periphery Model in the network closest to ideal model.
Part judging result is as shown in table 5:
The sealing abutment matrix that 5 part core point of table is constituted
According to table 5 it is found that 32 members are placed in the points such as core position, including node 1, node 26 by its result, by dividing
The above core node discovery is analysed, the point degree centrad of these forums member and intermediate centrad are relatively high greatly, the table in forum
It is now more active, almost the same result is presented with analysis result before.It can be seen that the communication between core node member
Will more frequently, the individual value played in forum is bigger.
In step s 4, calculate above-mentioned degree centrad, above-mentioned intermediate centrad, it is above-mentioned close to centrad and user whether
It is in weight of the nucleus when measuring network connection intensity.
Specifically, the present embodiment has determined 6 measurement indexs: corresponding point out-degree, corresponding point in analysis network connection intensity
In-degree, relatively intermediate centrad, in-degree close to centrad, out-degree close to user in centrad and Core-periphery Model whether
Nucleus.Based on these respective weights of index parameter.
On determining index weights, the present embodiment uses entropy assessment, can also be thinkable for those skilled in the art
Other methods.
The step of using entropy assessment parameter weight, is as follows:
Assuming that there is m to be evaluated object, n evaluation index, xij(1≤i≤m, 1≤j≤n) is evaluated object for i-th
Jth item index；
The first step is standardized decision matrix using range method:
Second step determines the entropy Hj for j-th of evaluation index that m-th is evaluated object:
Wherein:
Third step utilizes entropy parameter weight calculated above:
And meet
Based on above-mentioned calculation method, the weight for calculating index is as shown in table 6:
6 index weights of table
S5, according to the network connection intensity of above-mentioned weight calculation user.
Specific calculation method can be with are as follows:
If N={ n1, n2..., nmIndicate to participate in the subway forum user group of assessment, X={ X1, X2..., X6Indicate
6 indexs in this model.
Use WiIndicate each index relative to overall weight, it may be assumed thatThe then use of i-th of subway forum
The network connection intensity at family are as follows:
Wherein:
XiIndicate the network connection intensity of i-th of user；
xijIndicate the jth item index of i-th of user.
Calculated based on network connection intensity of the above-mentioned formula to user, partial results are as shown in table 7:
7 results of measuring of table
According to the above results, the embodiment of the present invention can accurately analyze the network connection intensity of user.
The embodiment of the invention provides a kind of analytical equipments of network connection intensity, comprising:
Data acquisition module, for obtaining the reply data of user；
Centrad module, for calculating the centrad of user according to above-mentioned reply data, above-mentioned centrad includes: in a degree
Heart degree, intermediate centrad and close to centrad；
User area judgment module judges user region for the Core-Periphery Structure model based on pre-training, on
Stating region includes: nucleus and fringe region；
Network connection intensity computing module, for calculating point degree centrad, intermediate centrad, being close to centrad and user
The no weight for being in nucleus when measuring network connection intensity；According to the network connection intensity of above-mentioned weight calculation user.
In conclusion compared with prior art, have it is following the utility model has the advantages that
The embodiment of the present invention calculates the centrad of user for the reply data of user, wherein centrad includes following several
Seed type: point degree centrad, intermediate centrad and close to centrad；The Core-Periphery Structure model based on pre-training is sentenced simultaneously
Disconnected user region, including nucleus and fringe region；Calculate point degree centrad, centre centrad, close to centrad and
Whether user is in weight of the nucleus when measuring network connection intensity；Network connection according to weight calculation user is strong
Degree, therefore the embodiment of the present invention can be from the network of two angle analysis users of centrad attribute and user region of user
Bonding strength, and obtain specific calculated value, it can accurately analyze network connection intensity.Meanwhile being connected according to calculated network
High-value user can be identified by connecing intensity, and enterprise or government can efficiently extract the information of high-value user, so that
It works more efficient.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to
Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.In the absence of more restrictions, the element limited by sentence " including one ... ", it is not excluded that
There is also other identical elements in the process, method, article or apparatus that includes the element.
The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although with reference to the foregoing embodiments
Invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features；And these modification or
Replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution.
Claims (10)
1. a kind of analysis method of network connection intensity, which comprises the following steps:
Obtain the reply data of user；
The centrad of user is calculated according to the reply data, the centrad includes: a degree centrad, intermediate centrad and connects
Nearly centrad；
Core-Periphery Structure model based on pre-training judges that user region, the region include: nucleus and edge
Region；
It calculates described degree centrad, the intermediate centrad, described exist close to whether centrad and user are in nucleus
Measure weight when network connection intensity；
According to the network connection intensity of the weight calculation user.
2. analysis method as described in claim 1, which is characterized in that measurement index packet when described degree centrad calculates
It includes: corresponding point out-degree and corresponding point in-degree；Measurement index when the intermediate centrad calculates includes: relatively intermediate centrad；
Measurement index when calculating close to centrad includes: in-degree close to centrad, out-degree close to centrad.
3. analysis method as claimed in claim 2, which is characterized in that the calculation method of described degree centrad are as follows:
The number for being pointing directly at the other users of user is obtained, corresponding point in-degree is obtained；
The number for the other users that user is pointing directly at is obtained, corresponding point out-degree is obtained；
Point degree centrad is obtained based on the corresponding point in-degree and the corresponding point out-degree.
4. analysis method as claimed in claim 2, which is characterized in that the calculation method of the intermediate centrad are as follows:
It obtains user and appears in the number in the most short internuncial pathway of any two other users, obtain relatively intermediate centrad；
Intermediate centrad is obtained based on the relatively intermediate centrad.
5. analysis method as claimed in claim 2, which is characterized in that the calculation method close to centrad are as follows:
The shortest path sum of the distance that each other users are pointing directly at user is obtained, obtains in-degree close to centrad；
The shortest path sum of the distance that user is pointing directly at each other users is obtained, obtains out-degree close to centrad；
It is obtained close to centrad and the out-degree close to centrad close to centrad based on the in-degree.
6. analysis method as claimed in claim 2, which is characterized in that the calculation method packet of the network connection intensity of the user
It includes:
Calculate corresponding point out-degree, corresponding point in-degree, relatively intermediate centrad, in-degree close to centrad, out-degree close to centrad and
Whether user is in the weight of nucleus in Core-periphery Model；
According to the weight calculation network connection intensity, calculation formula are as follows:
Wherein:
XiIndicate the network connection intensity of i-th of user；
xijIndicate the jth item index of i-th of user；
wiIndicate weight of each index relative to overall performane, i.e.,
7. analysis method as described in claim 1, which is characterized in that the method for calculating weight includes: entropy assessment.
8. a kind of analytical equipment of network connection intensity characterized by comprising
Data acquisition module, for obtaining the reply data of user；
Centrad module, for calculating the centrad of user according to the reply data, the centrad includes: a degree center
Degree, intermediate centrad and close to centrad；
User area judgment module judges user region, the area for the Core-Periphery Structure model based on pre-training
Domain includes: nucleus and fringe region；
Network connection intensity computing module, for calculating described degree centrad, the intermediate centrad, described close to centrad
Weight of the nucleus when measuring network connection intensity whether is in user；Connected according to the network of the weight calculation user
Connect intensity.
9. analytical equipment as claimed in claim 8, which is characterized in that in the centrad module, described degree centrad
Measurement index includes: corresponding point out-degree and corresponding point in-degree；The measurement index of the intermediate centrad includes: relatively intermediate center
Degree；The measurement index close to centrad includes: in-degree close to centrad, out-degree close to centrad.
10. analytical equipment as claimed in claim 8, which is characterized in that in the network connection intensity computing module, the use
The calculation method of the network connection intensity at family includes:
Calculate corresponding point out-degree, corresponding point in-degree, relatively intermediate centrad, in-degree close to centrad, out-degree close to centrad and
In Core-periphery Model user whether nucleus weight；
According to the weight calculation network connection intensity, calculation formula are as follows:
Wherein:
XiIndicate the network connection intensity of i-th of user；
xijIndicate the jth item index of i-th of user；
wiIndicate weight of each index relative to overall performane, i.e.,
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