CN106530097A - Oriented social network key propagation node discovering method based on random walking mechanism - Google Patents
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Abstract
The invention discloses an oriented social network key propagation node discovering method based on a random walking mechanism. The method comprises the steps that a random walking starting node is necessarily selected; for the propagation of positive network information, the starting node can be randomly selected from a network; and for the propagation of negative network information, a node which receives the information can be randomly selected as the starting node, so as to improve prevention and control effects of the propagation of the negative network information. According to the invention, the simple random walking mechanism is used; a small amount of local node information is acquired, and a key node influencing information propagation in an oriented social network can be found; the method is simple and efficient, is not limited by the network scale, and can be applied to a variety of large-scale oriented social networks; the slightly modified method can be applied to a non-directional social network and other different types of information propagation networks; and the method contributes to designing an information network propagation protocol with efficient performance, and can be used for prevention and control of the propagation of rumors and other harmful information in networks.
Description
【Technical field】
The present invention relates to a kind of oriented social networks based on random walk mechanism is crucial to propagate node discovery method.
【Background technology】
In recent years, with the fast development of the social networks such as microblogging, blog, community forum, wechat, Email, relatively
In traditional media, by means of social networks fast propagation, and can reach including positive and negative various information
Very wide spread scope and very big prevalence.Comparatively speaking, the oriented social networks such as microblogging is easy to use
Fast, and not limited by aspects such as time, regions, user can be allowed to give full expression to the viewpoint of oneself, different meanings are delivered
See, therefore be more exposed to the favor of most of users, corresponding its effect in terms of Information Communication is also more projected.Such as,
Various rumours are propagated by means of microblogging, and the daily life for giving people causes larger negative effect.Certainly, governments at all levels
Also various positive information can be issued using microblog, to disclose the false of rumour itself, so as to reach the purpose refuted a rumour.
In order that the social network information such as microblogging is propagated preferably serves society and daily life, we are accomplished by grasping
In which the mechanism of transmission, and this foundation is on the basis of micro-blog information Transmission dynamic behavioral study.
It is deep understand social network information propagation law on the basis of, we just targetedly can take measures plus
The propagation of fast positive information, can also equally be designed for the effective prevention mechanism for suppressing negative social network information to propagate.Net
In network, the crucial determination for propagating node is extremely important for the propagation law of profound understanding social network information, therefore the research
The concern of lot of domestic and foreign researcher is received, and proposes various algorithms for finding crucial propagation node in network, but this
A little algorithms more or less come with some shortcomings part, such as, some algorithms it should be understood that the global information of network, and some algorithms
Complexity it is larger etc..It is additionally, the forming process of social networks understands by analysis, many social networks such as microblogging, rich
Visitor etc. is directed networkses, i.e., information is always broadcast to its neighbor node, phase between only two nodes from a node
Mutually pay close attention to, information can the two-way propagation between the two nodes, in existing discovery network, crucial node algorithm of propagating is related to
Directed networkses it is even more fewer.Therefore, either in order to better control over the propagation of negative micro-blog information, or in order to plus
The propagation of fast front micro-blog information, designs the crucial algorithm for propagating node in can be used in finding the directed networkses such as microblogging and extremely closes
It is important.For designed crucial node of propagating finds algorithm, need using the side such as Monte-Carlo Simulation and true environment operation
Method carries out comprehensive verification to the algorithm, it is ensured which is accurate, reasonable, efficient.
【The content of the invention】
Present invention aims to the crucial node of propagating of existing network finds that algorithm is present in oriented social networks
Problem and deficiency, there is provided a kind of oriented social networks based on random walk mechanism is crucial to propagate node discovery method, the party
Method makes full use of the flexibility of random walk mechanism, and only it should be understood that the local message of network node, algorithm itself is not only
Simply, efficiently, and its autgmentability is also relatively good, it is modified slightly can be used for undirected social networks, nonoriented communication network etc..
For realizing above-mentioned target, the present invention is employed the following technical solutions and is achieved：
The crucial propagation node discovery method of oriented social networks based on random walk mechanism, comprises the following steps：
1) selection of random walk start node：For the propagation of positive information, a node is arbitrarily chosen from network
As the start node of migration；For the prevention and control of negative report, a node for having received information is arbitrarily chosen as migration
Start node；
2), after determining the start node of migration, walk process is opened from the start node；In whole walk process, begin
Record eventually and possess the more node of neighbor node, till migration reaches default step number.
The present invention is further improved by：
The step 2) concrete grammar it is as follows：
Step number n of random walk 2-1) is preset, and in walk process, needs the crucial propagation number of nodes m for storing；
2-2) No. ID and its neighbor node quantity of record start node, and start migration, Mei Yibu from the start node
All possess the node of maximum neighbor node quantity in the neighbor node of migration to present node, and record No. ID of the node and its
Neighbor node quantity, until the number of nodes being recorded is m；From the beginning of the m+i node, with m node being above recorded
The minimum node of middle neighbor node quantity is compared, if the neighbor node quantity that the m+i node possesses is greatly, is just saved with this
Point replaces the minimum node of that neighbor node quantity in m node, continues migration until the step number of migration is n；Wherein, i ∈ N
+, N+ is positive integer collection；
If the neighbor node quantity of node 2-3) being recorded is 0, retreats two steps and selection possesses neighbor node quantity
Continue migration for secondary big node, until the step number of migration is n；If having returned to start node, start node is chosen from new
And from step 2-1) start new walk process.
The crucial of step number n of the random walk and storage propagates number of nodes m, according to actual needs and should take into account
Efficiency of algorithm is arranging.
All the time what is recorded in the random walk process is the node for possessing larger neighbor node quantity.
Compared with prior art, the invention has the advantages that：
The invention discloses a kind of oriented social networks based on random walk mechanism is crucial to propagate node discovery method, head
First need to complete the selection of random walk start node, for the propagation of the front network information, start node can be from network
Randomly select；For the propagation of the negative network information, a node for having received information can be randomly choosed as starting section
Point, purpose are exactly to improve the control effect of negative spreading network information.
Further, the present invention in random walk process, all record in the neighbor node of present node by each step, adjacent
The most node of number of nodes is occupied, this shows that algorithm can obtain the key node for affecting spreading network information；When running into neighbours
During the most node of number of nodes, it is not to store the node immediately, but compared with m stored node, subsequently
Determine whether to store the node.The present invention obtains the crucial propagation node in network by adopting simple random walk mechanism,
The algorithm is highly susceptible to being realized by software, and positive information that can be suitable for social networks is propagated, network public-opinion is propagated
The crucial discovery for propagating node in prevention and control and other communication networks.
Further, the present invention takes into account algorithm reliability and efficiency of algorithm optimization simultaneously, in whole random walk process
Be not in the node of repetition migration, while being also not in endless loop and passless situation.Additionally, the present invention and network
Scale size it is unrelated, by adjust migration step number be applicable to the social networks of various scales among.
【Specific embodiment】
Below the present invention is described in further detail：
Oriented social networks of the present invention based on random walk mechanism is crucial to propagate node discovery method, including following step
Suddenly：
1) selection of random walk start node：For the propagation of the front network information, arbitrarily one is chosen from network
Start node of the node as migration；For the prevention and control of the negative network information, arbitrarily choose a node for having received information and make
For the start node of migration.
2) after determining the start node of migration, it is possible to open walk process from the start node.In walk process,
All the time record and possess those more nodes of neighbor node, till migration reaches default step number.
The step is specifically included：
Step number n of random walk 2-1) is preset, and in walk process, needs the crucial propagation number of nodes m for storing；
2-2) No. ID and its neighbor node quantity of record start node, starts migration from start node, and each step is all swum
Walk into the neighbor node of present node to possess the node of maximum neighbor node quantity, and record No. ID and its neighbours of the node
Number of nodes, until the number of nodes being recorded is m.Start from m+i (i ∈ N+, N+ are positive integer collection) individual node, and above
In m node being recorded, the minimum node of neighbor node quantity is compared, if the neighbor node number that the m+i node possesses
Amount is big, then just replace that minimum node of neighbor node quantity in m node with the node, continue thereafter with migration until migration
Step number be n；
If the neighbor node quantity for 2-3) being recorded node is 0, retreats two steps and selection possesses neighbor node quantity and is
Secondary big node continues migration, until the step number of migration is n；If having returned to start node, start node is chosen simultaneously from new
From step 2-1) start new walk process.
During random walk, step number n and storage key node number two kinds of parameters of m of migration is respectively provided with, its
In parameter n determine the depth of migration, the parameter can affect the time complexity of algorithm；And parameter m then determines algorithm
Validity, while can also affect the efficiency of algorithm；Specifically include following steps：
A, network key proposed by the present invention propagate node find algorithm in, it is contemplated that the neighbor node quantity of node
Size, this represent the out-degree of the node, because comparing with in-degree, the impact that the out-degree of node is propagated to social network information is more
Greatly；
The selection of B, start node：First, for the propagation of positive information in network, arbitrarily choosing a section from network
Point is used as start node；Second, for the prevention and control of negative report in network, arbitrarily choosing a node conduct for having received information
Start node；
C, tax initial value：Step number n of setting random walk, and in walk process, need the crucial propagation number of nodes for storing
m；
D, storing initial key node：No. ID of record start node and its neighbor node quantity, from the beginning of start node
Migration, possesses the node of maximum neighbor node quantity, and records the section in each step all migration to the neighbor node of present node
No. ID and its neighbor node quantity of point, until the number of nodes being recorded is m；
E, renewal key node：Start from m+i (i ∈ N+, N+ are positive integer collection) individual node, with the m being above recorded
In individual node, the minimum node of neighbor node quantity is compared, if the neighbor node quantity that the m+i node possesses is greatly, just
Replace that minimum node of neighbor node quantity in the m node for having stored with the node, continue migration until the step of migration
Number is n；
F, in whole walk process, if the neighbor node quantity of the node being recorded be 0, retreat two steps and selection gather around
There is neighbor node quantity to be that time big node continues migration, until the step number of migration is n；If having returned to start node, from
New start node of choosing starts new walk process.
In social network information communication process, the key node in network plays important work to the propagation characteristic of information
With.Relative to the in-degree of node, out-degree can more affect propagation rate and final prevalence of information etc..Therefore, originally
The foundation that invention is recorded using the neighbor node quantity (as node out-degree) of node as node.This is because, neighbor node
The bigger out-degree for representing the node of quantity is bigger, will play the part of more importantly role during Information Communication.
The m key node stored in the present invention is dynamic change, each step of random walk can all replace m it is crucial
In node, that minimum node of neighbor node quantity, remains that the neighbor node quantity that recorded node possesses is larger
, this is effectively important guarantee of the invention.
The present invention determines the step number of random walk and the key node quantity of storage first according to real network environment, subsequently
The key node of random walk real-time update record is carried out, comprehensive purpose is to enable the invention to obtain Fiel as much as possible
The key node of Information Communication is affected in handing over network.
No. ID and its neighbor node quantity of key node during random walk, is only stored, and each step is only
Replace that minimum node of neighbor node quantity in stored node.The present invention is by using simply, rationally effectively
Random walk rule, devises and can obtain the crucial propagation node algorithm of effective social networks.The algorithm is easy to software realization,
The research of the aspects such as social network information propagation, network public-opinion propagation, network communication protocol efficiency can be used widely.
The present invention has taken into full account the optimization design of the practicality and efficiency of algorithm.It is as a result of back-off mechanism, whole
Individual random walk process is not in endless loop or passless situation.The applied environment of algorithm will not to network size
Ask, with stronger practicality.
The present invention has fully incorporated the advantage of various existing Random Walk Algorithms, has deeply considered true social network information
Have the special feature that in communication process, can effectively obtain the key node in true social networks.Additionally, the present invention also has knot
Structure is simple, the speed of service is fast, low complex degree and it is preferably portable the features such as, be completely suitable for real-life all kinds of
Prevention and control or the propagation of positive information that in social networks, negative report is propagated.
Above content technological thought only to illustrate the invention, it is impossible to which protection scope of the present invention is limited with this, it is every to press
According to technological thought proposed by the present invention, any change done on the basis of technical scheme, claims of the present invention is each fallen within
Protection domain within.
Claims (4)
1. the crucial propagation node discovery method of oriented social networks based on random walk mechanism, it is characterised in that including following
Step：
1) selection of random walk start node：For the propagation of positive information, a node conduct is arbitrarily chosen from network
The start node of migration；For the prevention and control of negative report, a node for having received information is arbitrarily chosen as the starting of migration
Node；
2), after determining the start node of migration, walk process is opened from the start node；In whole walk process, remember all the time
Possess the more node of neighbor node under record, till migration reaches default step number.
2. the oriented social networks based on random walk mechanism according to claim 1 is crucial propagates node discovery method,
Characterized in that, the step 2) concrete grammar it is as follows：
Step number n of random walk 2-1) is preset, and in walk process, needs the crucial propagation number of nodes m for storing；
2-2) No. ID and its neighbor node quantity of record start node, and start migration from the start node, each step is all swum
Walk into the neighbor node of present node to possess the node of maximum neighbor node quantity, and record No. ID and its neighbours of the node
Number of nodes, until the number of nodes being recorded is m；It is from the beginning of the m+i node, adjacent with m node being above recorded
Occupy the minimum node of number of nodes to be compared, if the neighbor node quantity that the m+i node possesses is big, with regard to the node generation
For the node that neighbor node quantity in m node is minimum, continue migration until the step number of migration is n；Wherein, i ∈ N+, N+
It is positive integer collection；
If the neighbor node quantity of node 2-3) being recorded is 0, it is secondary to retreat two steps and select to possess neighbor node quantity
Big node continues migration, until the step number of migration is n；If having returned to start node, from it is new choose start node and from
Step 2-1) start new walk process.
3. according to the crucial propagation node discovery method of the oriented social networks based on random walk mechanism in claim 1, its
It is characterised by, step number n of the random walk and the crucial of storage propagate number of nodes m, should be according to actual needs and simultaneous
Turn round and look at efficiency of algorithm to arrange.
4. according to the crucial propagation node discovery method of the oriented social networks based on random walk mechanism in claim 1, its
It is characterised by, what is recorded in the random walk process all the time is the node for possessing larger neighbor node quantity.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109657160A (en) * | 2018-12-29 | 2019-04-19 | 中国人民解放军国防科技大学 | Method and system for estimating incoming degree information based on random walk access frequency number |
| WO2019095858A1 (en) * | 2017-11-17 | 2019-05-23 | 阿里巴巴集团控股有限公司 | Random walk method, apparatus and device, and cluster-based random walk method, apparatus and device |
| CN112465301A (en) * | 2020-11-06 | 2021-03-09 | 山东大学 | Edge smart power grid cooperation decision method based on differential privacy mechanism |
| CN112765329A (en) * | 2020-12-31 | 2021-05-07 | 清华大学 | Method and system for discovering key nodes of social network |
| CN112800301A (en) * | 2021-03-19 | 2021-05-14 | 湖南人文科技学院 | Public opinion big data processing system and method |
| CN114297572A (en) * | 2022-01-06 | 2022-04-08 | 中国人民解放军国防科技大学 | Method and device for identifying node propagation influence in social network and computer equipment |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546230A (en) * | 2010-12-08 | 2012-07-04 | 中国科学院声学研究所 | Overlay-network topological optimization method in P2P (Peer-To-Peer) streaming media system |
| CN104778213A (en) * | 2015-03-19 | 2015-07-15 | 同济大学 | Social network recommendation method based on random walk |
-
2016
- 2016-10-11 CN CN201610888035.2A patent/CN106530097B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546230A (en) * | 2010-12-08 | 2012-07-04 | 中国科学院声学研究所 | Overlay-network topological optimization method in P2P (Peer-To-Peer) streaming media system |
| CN104778213A (en) * | 2015-03-19 | 2015-07-15 | 同济大学 | Social network recommendation method based on random walk |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11074246B2 (en) | 2017-11-17 | 2021-07-27 | Advanced New Technologies Co., Ltd. | Cluster-based random walk processing |
| WO2019095858A1 (en) * | 2017-11-17 | 2019-05-23 | 阿里巴巴集团控股有限公司 | Random walk method, apparatus and device, and cluster-based random walk method, apparatus and device |
| TWI709049B (en) * | 2017-11-17 | 2020-11-01 | 開曼群島商創新先進技術有限公司 | Random walk, cluster-based random walk method, device and equipment |
| CN109657160A (en) * | 2018-12-29 | 2019-04-19 | 中国人民解放军国防科技大学 | Method and system for estimating incoming degree information based on random walk access frequency number |
| CN109657160B (en) * | 2018-12-29 | 2023-01-06 | 中国人民解放军国防科技大学 | Method and system for estimating incoming degree information based on random walk access frequency number |
| CN112465301A (en) * | 2020-11-06 | 2021-03-09 | 山东大学 | Edge smart power grid cooperation decision method based on differential privacy mechanism |
| CN112465301B (en) * | 2020-11-06 | 2022-12-13 | 山东大学 | Edge smart power grid cooperation decision method based on differential privacy mechanism |
| CN112765329B (en) * | 2020-12-31 | 2022-07-05 | 清华大学 | Method and system for discovering key nodes of social network |
| CN112765329A (en) * | 2020-12-31 | 2021-05-07 | 清华大学 | Method and system for discovering key nodes of social network |
| CN112800301A (en) * | 2021-03-19 | 2021-05-14 | 湖南人文科技学院 | Public opinion big data processing system and method |
| CN112800301B (en) * | 2021-03-19 | 2023-10-31 | 湖南人文科技学院 | Public opinion big data processing system and method |
| CN114297572A (en) * | 2022-01-06 | 2022-04-08 | 中国人民解放军国防科技大学 | Method and device for identifying node propagation influence in social network and computer equipment |
| CN114297572B (en) * | 2022-01-06 | 2022-11-29 | 中国人民解放军国防科技大学 | Method and device for identifying node propagation influence in social network and computer equipment |
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