CN108092832A - A kind of social networks Virus Info suppressing method and system - Google Patents
A kind of social networks Virus Info suppressing method and system Download PDFInfo
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Abstract
The invention discloses a kind of social networks Virus Info suppressing method and system, including：Step (1)：Establish social networks；Step (2)：Determine whether that virus is propagated in social networks；If so, then enter step (3)；If it is not, continue to judge；Step (3)：Improved SIQR models are built, the parameter in model is set according to social networks viral transmission situation；Step (4)：Using the parameter in improved SIQR models, the equalization point of HIV suppression is calculated；Step (5)：According to equalization point, HIV suppression strategy is provided, virus is inhibited according to HIV suppression strategy.During virus outbreak, it can take a variety of effective measures will be within its transmission controe to minimum zone according to influence factor and the relation of threshold value.
Description
Technical field
The present invention relates to a kind of social networks Virus Info suppressing method and systems.
Background technology
With the fast development of information technology and network technology, social networks (SN) is able to rapid general in the world
And people can quickly and easily obtain miscellaneous information.At the same time, virus, rumour, Malware in social networks
Flames is waited also inevitably to appear in social networks.Therefore, the information propagation of social networks becomes research hotspot.
In the information Communication Research of social networks, complex network Dynamical model is generally used for reference, from nineteen twenty-seven
Kermack and McKendrick proposes storage model so far, and various infectious disease propagation models emerge in an endless stream.The researchs such as Kuperman
Communication process of the SIR models in small-world network；Man of virtue and ability is superfine and bear is prosperous etc. has studied SIR models is used in social networks
Information propagate, and carried out contrast simulation using emulation experiment and correlation model；The description of SIR models is applied to by Freeman
In concrete case and predict user behavior.
The content of the invention
In order to solve the deficiencies in the prior art, the present invention provides a kind of social networks Virus Info suppressing method and it is
System, with an improved SIQR models, (SIQR models are a kind of viral transmission models, and S, I, Q, R represent four class nodes respectively：Easy infection
Node S propagates node I, isolation node Q and immune node R), using Differential Model analysis and the equalization point of simulation improved model
Problem, and indicate the effective measures of control viral transmission.Research and control to this kind of viral transmission rule, are conducive to social activity
The development of dynamic law and perfect is propagated on network.
A kind of social network information suppressing method, including：
Step (1)：Establish social networks；
Step (2)：Determine whether that virus is propagated in social networks；If so, then enter step (3)；If not provided,
Then return to step (2) continues to judge；
Step (3)：Improved SIQR models are built, the parameter in model is carried out according to social networks viral transmission situation
Setting；
Step (4)：Using the parameter in improved SIQR models, the equalization point of HIV suppression is calculated；
Step (5)：According to equalization point, HIV suppression strategy is provided, virus is inhibited according to HIV suppression strategy.
Further, in the step (1)：
Assuming that social networks, including four kinds of nodes：Easy infection node S propagates node I, isolation node Q and immune node R；
Wherein, easy infection node S can be infected, and propagated node I and be infected, and can be passed and be propagated to neighbor node
Virus；It is the node for being forced blocking communication ability to isolate node Q, does not possess transmitted virus ability, can not be infected；It is immune
Node R cannot be infected.
Further, in the step (3)：
(301)：T moment node total amount remains constant K in social networks, i.e.,：
S (t)+I (t)+Q (t)+R (t)=K；
Wherein, K represents total node number mesh, and S (t) represents t moment easy infection interstitial content, and I (t) represents that t moment propagates section
It counts out, Q (t) represents t moment isolation interstitial content, and R (t) represents that interstitial content is immunized in t moment；
(302)：Newly added node is easy infection node S, and the new addition rate of newly added node is b；Easy infection node S's
The autonomous rate that exits is d；Easy infection node S, which is deactivated isolation and is converted into, isolates the probability of node Q for m；Each easy infection node S with
Infection rate λ and contact rate β, which is converted into, propagates node I；
(303)：With the conversion of easy infection node S, it is d to propagate the probability that node I is independently exited, and propagates node and is forced
The probability of isolation is α；
(304)：The probability that isolation node Q is independently exited is d, and isolation node Q is changed into the probability of immune node R as μ, every
The probability that immune node can not be changed into from node is γ；
(305)：After isolation node Q is converted into immune node R, it will not be immunized what node R independently exited by superinfection
Probability is d.
Further, in the step (4) HIV suppression equalization point R0：
Further, in the step (5),
Work as R0During ＜ 1, virus will disappear；Work as R0During ＞ 1, virus will be popular；
When viral prevalence, by increasing invalid isolation rate m and forced quarantine rate α, R is realized0The reduction of numerical value, so as to real
Now to the inhibition of virus；Alternatively,
When viral prevalence, by reducing spreading rate λ and contact rate β, R is realized0The reduction of numerical value, so as to fulfill to virus
Inhibition；Alternatively,
When viral prevalence, by increasing invalid isolation rate m and forced quarantine rate α, meanwhile, reduce spreading rate λ and contact
Rate β realizes R0The reduction of numerical value, so as to fulfill the inhibition to virus.
The HIV suppression strategy, further includes：
Easy infection node S is deactivated isolation because being contacted with propagating node I with probability m；
Whether the node for judging to be deactivated isolation is converted into immune node R, if so, just terminating；
If being not converted into immune node R, determine whether the node for being deactivated isolation actively exits, if actively
It exits, then terminates；If not exiting actively, compulsory withdrawal.
The node allow for：Server or mobile terminal.
The isolation node Q includes being infected segregate node and is not infected segregate section
Point.
The invalid isolation rate represents that not being infected number of nodes in isolation node accounts for all isolation number of nodes
Ratio；
The invalid immunization rate represents that isolation node during immune node is changed into, converts the number of nodes of failure
Amount accounts for the ratio of all quantity for participating in conversion node.
A kind of social network information suppression system, including：Memory, processor and storage on a memory, and are being located
The computer instruction run on reason device when the computer instruction is run by processor, completes the as above step described in either method
Suddenly.
Compared with prior art, the beneficial effects of the invention are as follows：
When virus or rumour are broken out in social networks, generally using isolation strategy, however often exist in the strategy
Invalid isolating problem, and node remains mobility in this process.For these problems, present invention improves over
SIQR models are introduced new addition rate, independently exit the parameters such as rate, invalid isolation rate, ground using complex network mean field theory
The existence and stability problem of equalization point are studied carefully, have disclosed between the factors such as spreading rate, the forced quarantine rate of viral (rumour)
Relation, reliability is verified by emulation experiment.The experimental results showed that viral transmission is determined by a threshold value, force
Isolation rate negative is on this threshold value.During virus outbreak, can a variety of effective measures be taken according to influence factor and the relation of threshold value
Within its transmission controe to minimum zone.
Description of the drawings
The accompanying drawings which form a part of this application are used for providing further understanding of the present application, and the application's shows
Meaning property embodiment and its explanation do not form the improper restriction to the application for explaining the application.
Fig. 1 is the flow chart of the present invention；
Fig. 2 is invalid isolation node state evolution diagram；
Fig. 3 is propagation node immunologic process figure；
Fig. 4 is the mechanism of transmission figure for improving SIQR models；
Fig. 5 corresponds to easy infection node ratio change curve for disease free equilibrium；
Fig. 6 is corresponded to for disease free equilibrium and is propagated node ratio change curve；
Fig. 7 corresponds to easy infection node ratio change curve for endemic equilibrium point；
Fig. 8 is corresponded to for endemic equilibrium point and is propagated node ratio change curve.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.It is unless another
It indicates, all technical and scientific terms that the present invention uses have leads to the application person of an ordinary skill in the technical field
The identical meanings understood.
As shown in Figure 1, a kind of social network information suppressing method, including：
Step (1)：Establish social networks；
Assuming that social networks, including four kinds of nodes：Easy infection node S propagates node I, isolation node Q and immune node R；
Wherein, easy infection node S can be infected, and transmitted virus can be passed to neighbor node by propagating node I, isolate node
Q does not possess transmitted virus ability, can not be infected, and immune node R cannot be infected；
Step (2)：Determine whether that virus is propagated in social networks；If so, then enter step (3)；If not provided,
Then return to step (2) continues to judge；
Step (3)：Improved SIQR models are built, the parameter in model is carried out according to social networks viral transmission situation
Setting；
(301)：T moment node total amount remains constant K in social networks, i.e.,：
S (t)+I (t)+Q (t)+R (t)=K；
Wherein, K represents total node number mesh, and S (t) represents t moment easy infection interstitial content, and I (t) represents that t moment propagates section
It counts out, Q (t) represents t moment isolation interstitial content, and R (t) represents that interstitial content is immunized in t moment；
(302)：Newly added node is easy infection node S, and the new addition rate of newly added node is b；Easy infection node S's
The autonomous rate that exits is d；Easy infection node S, which is deactivated isolation and is converted into, isolates the probability of node Q for m；Each easy infection node S with
Infection rate λ and contact rate β, which is converted into, propagates node I；
(303)：With the conversion of easy infection node S, it is d to propagate the probability that node I is independently exited, and propagates node and is forced
The probability of isolation is α；
(304)：The probability that isolation node Q is independently exited is d, and isolation node Q is changed into the probability of immune node R as μ, every
It can not be changed into immune node from node and the probability of protrusion is γ；
(305)：After isolation node Q is converted into immune node R, it will not be immunized what node R independently exited by superinfection
Probability is d.
Step (4)：Using the parameter in improved SIQR models, the equalization point R of HIV suppression is calculated0；
Step (5)：According to equalization point, HIV suppression strategy is provided；
Work as R0During ＜ 1, virus will disappear；Work as R0During ＞ 1, virus will be popular；
When viral prevalence, by increasing invalid isolation rate m and forced quarantine rate α, R is realized0The reduction of numerical value, so as to real
Now to the inhibition of virus；Alternatively,
When viral prevalence, by reducing spreading rate λ and contact rate β, R is realized0The reduction of numerical value, so as to fulfill to virus
Inhibition；Alternatively,
When viral prevalence, by increasing invalid isolation rate m and forced quarantine rate α, meanwhile, reduce spreading rate λ and contact
Rate β realizes R0The reduction of numerical value, so as to fulfill the inhibition to virus.
The figure embodies social network information and inhibits flow.Social networks is initially set up, user node quantity is gradually stablized
Within the specific limits, then detect always with the presence or absence of viral (or improper speech, rumour etc.) in the social networks, if depositing
Improved SIQR models are then being built, the parameter in model is being set according to actual conditions, and are being calculated based on Differential Model
The equalization point of HIV suppression finally, HIV suppression strategy is provided according to equalization point.
As shown in Fig. 2, the figure describes the evolutionary process of invalid isolation node.In social networks, invalid isolation can not
It avoids.For example, easy infection node due to browsed propagate node content or propagate node between communicate and by
It is mistakenly considered to need to isolate, is evolved into isolation node, and actually such node is possible to not virus infection.It is at this point, invalid
If isolation node is evolved into immune node, terminate；Otherwise, which can voluntarily select to exit network or because that can not drill
Immune node is turned to be exited by force.
As shown in figure 3, the figure describes the immunologic process for propagating node.When virus generates and propagates, easy infection node
Propagation node can be evolved into due to spreading rate λ and contact rate β, isolation section can be evolved into forced quarantine rate α by then propagating node
Point, further, isolation node are evolved into immune node with immunization rate μ, and immunologic process terminates.
The Information Propagation Model of SN is usually established the .SIQR models on the basis of Epidemic Model and is passed by complex network
Dynamics basic knowledge is broadcast, on the basis of classical SIS and SIR propagation models, it is contemplated that the factors such as isolation, immune.This hair
The bright main SIQR models having studied under the conditions of improvement isolation.
SIQR models introduce isolation strategy on the basis of SIR models and obtain, and the propagation node in SIR models and exempt from
A new class of node is added between epidemic disease node -- isolation node.Therefore, mainly there are four class nodes in SIQR models：It is susceptible
It contaminates node, propagate node, isolation node and immune node.All kinds of nodes shared ratio in a network, does not stop to change at any time.
During virus outbreak, part of nodes virus infection is isolated, and becomes isolation node and no longer possesses viral transmission ability.
Finally, isolation node is effectively controlled and becomes immune node or can not remove virus and exit network, and immune node will not
By superinfection.
SIQR models are considered not comprehensive enough although it is contemplated that isolation condition.Section is newly added in one side social networks
It point and exits node and is occurring always, the addition of node and exit and will not stop due to the prevalence of virus.On the other hand for prominent
The virus so broken out, when taking quarantine measures, often with hysteresis quality, so as to cause the appearance of invalid isolating problem.
In view of the above-mentioned problems, present invention improves over SIQR propagation models, it is contemplated that invalid isolated instances are established with new
Addition rate and the propagation model for independently exiting rate.Total node number amount is constant during the model hypothesis viral prevalence.Because being saved in model
Point except it is autonomous exit it is outer can also be exited due to virus can not be removed, so to keep node total number constant, new addition rate is higher than certainly
Master exits rate.
Newly added node is easy infection node in the model.Easy infection node, propagation node, isolation section in model
Point, immune node, which are present with, independently exits phenomenon.Its mechanism of transmission is (see Fig. 4) as shown below：
(1) random time t moment node total amount remains a constant K, i.e. S (t)+I (t)+Q (t)+R (t) in social networks
=K.
(2) node that new addition rate is b is added in easy infection node, and the probability that easy infection node independently exits is d.Easily
Infection node, which is deactivated isolation and is converted into, isolates the probability of node for m, and part easy infection node is by spreading rate λ's and contact rate β
Influence is converted into propagation node.
(3) with the conversion of easy infection node, it is also d to propagate the probability that node independently exits.Node is propagated to be effectively isolated
Probability be α.
(4) probability that all isolation node independently exits is d.Isolation node can not be changed into immune node and exit general
Rate is γ, and successful transformation is that the probability of immune node is μ.
(5), will not be by superinfection after isolation node is changed into immune node, the probability that immune node independently exits is d.
According to the transforming relationship between all kinds of nodes in mechanism of transmission, improvement can be write out according to complex network mean field theory
The differential equation of SIQR models (see formula 1).
Wherein, K represents total node number mesh, and S (t) represents t moment easy infection interstitial content, and I (t) represents that t moment propagates section
It counts out, Q (t) represents t moment isolation interstitial content, and R (t) represents that interstitial content is immunized in t moment, and λ represents infection rate, and β is represented
Contact rate, b represent new addition rate, and d represents independently to exit rate, and m represents invalid isolation rate, and α represents forced quarantine rate, and μ expressions are exempted from
Epidemic disease rate, γ represent invalid immunization rate；
This improved model adds new addition rate, independently exits the factors such as rate, the mobility of node is maintained, so pole has
It is likely to occur endemic equilibrium point.Viral prevalence and Disappearance Scenarios can be analyzed according to this equalization point.For this reason, it may be necessary to it studies susceptible
It contaminates node (S) and propagates the condition of node (I).Using the first two equation in formula (1), the flat of the improved model can be analyzed
Weighing apparatus point problem.
The planar system of the first two equation composition is in formula (1)：
Wherein, (S, I)={ (S, I) 0≤S≤K, 0≤I≤K, S+I≤K }
To seek the equalization point of the planar system (formula 2), it is 0 to make its right end, so as to acquire two groups of solution X that may be present1
And X2：
If this two groups of solutions are respectively stable disease free equilibrium and endemic equilibrium point, Correlative Influence Factors are adjusted and come
The propagation of virus is controlled, and reduces its harm come to Netowrk tape as far as possible.
If R0For threshold value, orderWork as R0During ＜ 1, planar system is only unique in the D of region
Equalization point X1, so as to can be determined that X by the symbol of its characteristic equation coefficient p, q1Stability.
From formula (3) and formula (4), point X1It is locally asymptotic stability.Again due to only having only equalization point in region
X1, it is impossible to there is Closed curve, and the path that planar system is sent out of region D is impossible to run off D.Therefore, the Dian areas
Globally asymptotic in the D of domain.
It means that no matter initial easy infection node is how many in total node, virus all will not be popular, but gradually disappears
It loses.X1It is exactly the disease free equilibrium of the model.
WhenR0During ＞ 1, planar system (formula 2) removes disease free equilibrium X in the D of region1Outside, there is a Positive balance point X2.This
When, due toPoint X1It is uncertain.
From formula (5) and formula (6), point X2It is local stability.Region D is that the forward direction of planar system (formula 2) is constant
Collection, and there is no the Closed curves of the planar system in D.And then point X2The Globally asymptotic in the D of region.
It means that once there is propagation node, virus will be popular.Finally, the quantity of easy infection node and propagation node
X will be stabilized to respectively2Solution and form endemic disease.Point X2It is exactly the endemic equilibrium point of the model.
In conclusion work asR0During ＜ 1, virus fades away；WhenR0During ＞ 1, virus is by prevalence and ultimately forms endemic disease.
And work asR0When=1, the threshold value whether virus disappears is to discriminate between.
In improved SIQR models, to embody the dynamic of social networks node, the addition of node and to exit be always
Occur, be similarly to the birth and death of human world.When virus outbreak, the new addition rate of node independently exits rate, passes
It is as shown in table 2 to broadcast the parameter settings such as rate, contact rate, invalid isolation rate, forced quarantine rate and immunization rate.
Influenced contingency occur by number of nodes to avoid testing, this emulation experiment replaces actual node number with node accounting
Amount.When experiment starts (t=0), the ratio that easy infection number of nodes accounts for total node number is：S (0)=S/N=0.9；Propagate number of nodes
The ratio for accounting for total node number is：I (0)=I/N=0.1；Simulation time is 9 days.
2 parameter setting table of table
Known by above-mentioned theory analysis result,R0=1 is to discriminate between the threshold value of virus disappearance or prevalence.It is improved in the present invention
Parameter setting in SIQR models is as shown in table 2, and by new addition rate, to exit the factors such as rate constant, studies forced quarantine rate and threshold
Value R0Between relation.By and experiment in each constant constant value, easily calculate when forced quarantine rate value be 0.25
When, R0For viral prevalence, the threshold value 1 to disappear.
It is full at this time if forced quarantine rate is respectively 0.30,0.35,0.40,0.45,0.50,0.55 in Fig. 5 and Fig. 6
FootR0＜ 1, Fig. 5 are easy infection node ratio with time increased change curve, and Fig. 6 is propagates node as the time is increased
Change curve.From the figure, it can be seen that as time increases, easy infection number of nodes and propagation number of nodes reach stable shape
State, the ratio that easy infection number of nodes accounts for total node number stabilize to 1, and infection group population support accounts for total number of people purpose ratio stabilization
For 0.Finally, virus completely disappears, and all nodes are easy infection node in planar system (formula 2).And at this point,R0＜ 1 is put down
Weighing apparatus point is (1,0), this and disease free equilibrium X in theory analysis above1Calculated value fit like a glove.
In addition, as shown in Figure 5 and Figure 6, with the increase of forced quarantine rate, the time that node reaches disease free equilibrium gradually contracts
It is short.That is forced quarantine rate is bigger, and the time for reaching disease free equilibrium is shorter.
In Fig. 7 and Fig. 8, if forced quarantine rate is respectively 0.20,0.15,0.10,0.05,0.01, it is satisfied by this timeR0＞ 1,
Fig. 7 is easy infection node ratio with time increased change curve, and Fig. 8 is propagates node ratio with time increased variation
Curve.As shown in Figure 7 and Figure 8, as time increases, easy infection node ratio and propagation node ratio are in stablizing shape
State, but ratio is all higher than 0.SoR0During ＞ 1, viral transmission comes, and exists always.
As shown in Figure 7 and Figure 8, with the reduction of forced quarantine rate, node ratio reach time of endemic equilibrium point by
It is tapered short.When reaching stable state, easy infection node ratio is reduced with the reduction of forced quarantine rate；Propagate the ratio of node
Increase with the reduction with forced quarantine rate.
Theoretical and experimental results show the viral prevalence for burst, and there are threshold value R in SIQR propagation models are improved0。
WhenR0During ＜ 1, virus will disappear；WhenR0During ＞ 1, virus will be popular.Due in improved SIQR propagation models, newly adding
Enter rate, exit the parameters such as rate as uncontrollable factor, therefore, during viral prevalence, we can take certain measure, control other shadows
The value of the factor of sound, by R0Value be preferably minimized.In the case of virus disappears, R0Smaller, virus disappears faster；Viral prevalence
Afterwards, by reducing R0Value, also can effectively reduce spread scope.
Measure one：By R0Formula understand that m, α are and R0It is negatively correlated.With the increasing of invalid isolation rate and forced quarantine rate
Add, R0It is gradually reduced.So during viral prevalence, the propaganda work of virus precaution is carried out, increases node isolation speed and power
Degree increases forced quarantine rate, so as to more effectively effective control viral transmission.
Measure two：By R0Formula understand that λ, β are and R0It is directly proportional.With the reduction of spreading rate and contact rate, R0Gradually
Reduce.So can appeal that social networks node is enhanced your vigilance, enhance pre- anti-virus consciousness, rationally use proactive tool and hand
Section, so as to achieve the purpose that control viral transmission.
In social networks, the information of virus type is propagated soon, sudden strong.Some network models proposed at present, not
Consider invalid isolation and node mobility feature, for this purpose, present invention improves over SIQR models, using complex network mean field theory as
Foundation has studied the disease free equilibrium of the model and the existence of endemic equilibrium point and stability problem, and real using simulation
Test simulating, verifying its correctness.And virus extinction, the relation of popular threshold value and each influence factor are analyzed, and as theory
Basis proposes prevention and controls the measure of viral prevalence, so as to minimize the harm that virus is brought.Research work pair of the present invention
Viral prevention and control have important directive significance in social networks.
The foregoing is merely the preferred embodiments of the application, are not limited to the application, for the skill of this field
For art personnel, the application can have various modifications and variations.It is all within spirit herein and principle, made any repair
Change, equivalent substitution, improvement etc., should be included within the protection domain of the application.
Claims (10)
1. a kind of social network information suppressing method, it is characterized in that, including：
Step (1)：Establish social networks；
Step (2)：Determine whether that virus is propagated in social networks；If so, then enter step (3)；If it is not, it returns
Step (2) is returned to continue to judge；
Step (3)：Improved SIQR models are built, the parameter in model is set according to social networks viral transmission situation
It is fixed；
Step (4)：Using the parameter in improved SIQR models, the equalization point of HIV suppression is calculated；
Step (5)：According to equalization point, HIV suppression strategy is provided, virus is inhibited according to HIV suppression strategy.
2. a kind of social network information suppressing method as described in claim 1, it is characterized in that, in the step (1)：
Assuming that social networks, including four kinds of nodes：Easy infection node S propagates node I, isolation node Q and immune node R；
Wherein, easy infection node S can be infected, and propagated node I and be infected, and can be passed to neighbor node and be propagated disease
Poison；It is the node for being forced blocking communication ability to isolate node Q, does not possess transmitted virus ability, can not be infected；Immune section
Point R cannot be infected.
3. a kind of social network information suppressing method as claimed in claim 2, it is characterized in that, in the step (3)：
(301)：T moment node total amount remains constant K in social networks, i.e.,：
S (t)+I (t)+Q (t)+R (t)=K；
Wherein, K represents total node number mesh, and S (t) represents t moment easy infection interstitial content, and I (t) represents that t moment propagates number of nodes
Mesh, Q (t) represent t moment isolation interstitial content, and R (t) represents that interstitial content is immunized in t moment；
(302)：Newly added node is easy infection node S, and the new addition rate of newly added node is b；Easy infection node S's is autonomous
Rate is exited as d；Easy infection node S, which is deactivated isolation and is converted into, isolates the probability of node Q for m；Each easy infection node S is to infect
Rate λ and contact rate β, which is converted into, propagates node I；
(303)：With the conversion of easy infection node S, it is d to propagate the probability that node I is independently exited, and propagates node and is forced to isolate
Probability be α；
(304)：The probability that isolation node Q is independently exited is d, and isolation node Q is changed into the probability of immune node R as μ, isolation section
The probability that point can not be changed into immune node is γ；
(305)：After isolation node Q is converted into immune node R, will not the probability that node R independently exits be immunized by superinfection
For d.
4. a kind of social network information suppressing method as claimed in claim 3, it is characterized in that, virus suppression in the step (4)
The equalization point R of system0：
<mrow>
<msub>
<mi>R</mi>
<mn>0</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>&lambda;</mi>
<mi>&beta;</mi>
<mi>b</mi>
<mi>K</mi>
</mrow>
<mrow>
<mo>(</mo>
<mi>d</mi>
<mo>+</mo>
<mi>m</mi>
<mo>)</mo>
<mo>(</mo>
<mi>&alpha;</mi>
<mo>+</mo>
<mi>d</mi>
<mo>)</mo>
</mrow>
</mfrac>
<mo>.</mo>
</mrow>
5. a kind of social network information suppressing method as claimed in claim 4, it is characterized in that, in the step (5),
Work as R0During ＜ 1, virus will disappear；Work as R0During ＞ 1, virus will be popular；
When viral prevalence, by increasing invalid isolation rate m and forced quarantine rate α, R is realized0The reduction of numerical value, so as to fulfill right
The inhibition of virus.
6. a kind of social network information suppressing method as claimed in claim 5, it is characterized in that,
When viral prevalence, by reducing spreading rate λ and contact rate β, R is realized0The reduction of numerical value, so as to fulfill the suppression to virus
System.
7. a kind of social network information suppressing method as claimed in claim 5, it is characterized in that,
When viral prevalence, by increasing invalid isolation rate m and forced quarantine rate α, meanwhile, spreading rate λ and contact rate β is reduced,
Realize R0The reduction of numerical value, so as to fulfill the inhibition to virus.
8. a kind of social network information suppressing method as described in claim 1, it is characterized in that, the HIV suppression strategy, also
Including：
Easy infection node S is deactivated isolation because being contacted with propagating node I with probability m；
Whether the node for judging to be deactivated isolation is converted into immune node R, if so, just terminating；
If being not converted into immune node R, determine whether the node for being deactivated isolation actively exits, if actively moving back
Go out, then terminate；If not exiting actively, compulsory withdrawal.
9. a kind of social network information suppressing method as described in claim 1, it is characterized in that,
The isolation node Q includes being infected segregate node and is not infected segregate node；
The invalid isolation rate represents not being infected the ratio that number of nodes accounts for all isolation number of nodes in isolation node
Value；
The invalid immunization rate represents isolation node during immune node is changed into, and the number of nodes for converting failure accounts for
The ratio of all quantity for participating in conversion node.
10. a kind of social network information suppression system, it is characterized in that, including：Memory, processor and it is stored in memory
On, and the computer instruction run on a processor, when the computer instruction is run by processor, complete as above any right
It is required that the step of the method.
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