CN104317807A - Microblog user relationship network evolution model construction method based on network science - Google Patents
Microblog user relationship network evolution model construction method based on network science Download PDFInfo
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- CN104317807A CN104317807A CN201410493738.6A CN201410493738A CN104317807A CN 104317807 A CN104317807 A CN 104317807A CN 201410493738 A CN201410493738 A CN 201410493738A CN 104317807 A CN104317807 A CN 104317807A
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The invention discloses a microblog user relationship network evolution model construction method based on network science. The method comprises a network initialization stage and a network evolution generation stage, wherein the amount of initial nodes and the topological structure of an initial network are set in the network initialization stage, and the network evolution generation stage respectively adopts four mechanisms, i.e. stochastic growth, preferential attachment, stochastic attachment and reverse attachment. The invention fully considers a key evaluation mechanism in a microblog user relationship network formation process, can truly reflect the topological characteristics of the microblog user relationship network, has simple structure, is free from the restriction of network size, is suitable for analyzing various topological characteristics of a real microblog user relationship network and researching a transmission mechanism of various pieces of information in the microblog user relationship network, is favorable for optimizing the topological structure of a real network so as to improve the propagation efficiency of useful information, and is favorable for preventing and controlling network rumor propagation to lower harm brought by network rumors.
Description
Technical field
The invention belongs to the multi-disciplinary crossing domains such as computing machine, communication and network technology, be specifically a kind ofly used for information network, particularly a kind ofly can be used in the network evolution model construction method portraying various true microblog users relational network topological characteristic.
Background technology
Along with the fast development of internet, rumour is propagated in crowd by means of social media, its velocity of propagation is soon, the wide sound development not only directly jeopardizing internet of coverage, even return the normal civil order of country and bring reality or potential threat, " the horse boat lost contact passenger plane rumour ", " Kunming attack of terrorism rumour " of such as 2014, " aircraft has bomb rumour ", " H7N9 epidemic situation rumour " of 2013 etc.The countries in the world government comprising China all pays close attention to the harm that network gossip propagation causes, and takes many kinds of measures (comprise and making laws and regulations) and administer network rumour, but the propagation of network rumour is still of common occurrence.Therefore, domestic and international researcher proposes to be designed its technological means propagated of prevention and control by the mechanism of transmission of probing into network rumour inherence.
In the network platform spread rumors, owing to having facility, the feature such as real-time, quick, microblogging occupies most important position in network gossip propagation.Therefore, the mechanism of transmission studying network rumour mainly studies the mechanism of transmission of rumour in microblogging.If describe the communication process of microblogging rumour, just must by means of microblog users relational network, the node in network can be No. ID of microblog users, and limit is then situation about mutually paying close attention between microblog users.
Microblog users relational network is a kind of more common community network.According to ASSOCIATE STATISTICS, China's microblog users quantity is more than 300,000,000, and microblogging is bringing to daily life much simultaneously easily, and also bring very large negative effect to society, this mainly refers to that rumour can be propagated without restraint by means of microblogging.In order to reduce the harm that microblogging gossip propagation produces, domestic and international researcher expands further investigation to its propagation law, obtains some significant conclusions.But the network model adopted in these researchs is still BA network or its modification network, and seldom based on real microblog users relational network, this just significantly reduces practicality and the reference value of research.In addition, in order to design the Internet communication agreement of performance efficiency, improving the propagation efficiency of useful information, also needing the topological features studying network.Along with the continuous appearance of various large database and the fast lifting of computer process ability, make it possible to process mass network data, some research about microblogging gossip propagation mechanism has been based upon on real example network.But these are often restricted by the abstract network size out of True Data, and portable poor.Therefore, in order to effectively study the mechanism of transmission of microblogging rumour, just must construct relevant microblog users relational network evolutionary model, and the topological characteristic of this model is analyzed.
Summary of the invention
For above-mentioned defect or deficiency, the object of the present invention is to provide a kind of microblog users relational network evolutionary model building method of science Network Based, various mechanism in abundant fusion true microblog users relational network forming process, algorithm is simple, efficient and have good extendability.
For reaching above object, technical scheme of the present invention is:
Comprise the following steps:
1) setting nodes is as required m
0network model, all give Attraction Degree to each node, and determine the topological structure of initial network, random selecting node, makes this node and all the other m
0-1 node is all connected, forms initialization network model;
2) in network evolution process, when there being new node to add network, by random increase mechanism and preferential attachment mechanism, carry out new node interpolation, then by random connection mechanism and Opposite direction connection mechanism, node connection is carried out to the network after interpolation new node, form network evolution model.
Described step 2 specifically comprises:
2.1) random increase mechanism:
In each time interval, increase a new node in initialization network model, and choose m in initialization network model
1individual node connects, wherein, and m
1≤ m
0;
2.2) preferential attachment mechanism:
Obtain the probability Π of each node in initialization network model
i, Π
iexpression formula be
wherein k
jfor the degree of a jth node in initial network model, a
jfor the Attraction Degree of an initial network model jth node; According to the probability Π of each node
i, choose m from big to small
1node in individual initialization network model, sets up the directed connection being pointed to newly added node by selected node;
2.3) random connection mechanism:
M in random selecting initial network model
2individual node as terminal, according to the probability Π of all the other nodes in initial network model
i, choose m from big to small
2individual node as start node, and with selected m
2individual terminal sets up m successively
2bar directed connection; Wherein, m
2≤ m
0;
2.4) Opposite direction connection mechanism:
Predetermined probabilities q, according to default probability q, Opposite direction connection is added in the unidirectional connection newly-built to every bar.
Described Attraction Degree is arranged according to network model distribution, the distribution of described network model comprise be uniformly distributed, exponential distribution and power-law distribution.
The topological structure of described initial network comprises stelliform connection topology configuration and full-mesh topological structure.
Compared with the prior art, beneficial effect of the present invention is:
The invention discloses a kind of microblog users relational network evolutionary model building method of science Network Based, first initialization is carried out to network, random growth, preferential attachment, random connection and Opposite direction connection mechanism is adopted to complete the evolutionary process of whole network subsequently, thus make the present invention farthest can reflect the forming process of true microblog users relational network, portray the various statistical natures that live network has as much as possible.
Further, at microblog users relational network evolution generation phase, each time step has a node to join network, shows with this characteristic that network size increases at random; Mutually adding in the process paid close attention to, including and give priority to and pay close attention to two kinds of situations at random; The interpolation oppositely paid close attention to then is carried out with certain probability.The present invention adopts simple rule to construct to have the microblog users relational network of complex characteristics, is convenient to realize in the form of software, can be used in the research of the aspects such as the analysis of social media, public sentiment transmission controe and network communication efficiency.
Send out further, the present invention has carried out the optimal design of efficiency while raising practicality, avoid the appearance repeating establishment of connection and isolated node between two nodes, and the scale of the generating network that develops is unrestricted, can be used in requiring larger research environment to network size.
Accompanying drawing explanation
Fig. 1 is netinit algorithm flow schematic diagram of the present invention;
Fig. 2 is evolution algorithmic schematic flow sheet of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in detail.
The invention provides a kind of microblog users relational network evolutionary model building method of science Network Based, comprise the following steps:
1) setting nodes is as required m
0network model, all give Attraction Degree to each node, and determine the topological structure of initial network, random selecting node, makes this node and all the other m
0-1 node is all connected, forms initialization network model;
Wherein, described in degree of drawing may meet different distributions, to be such as uniformly distributed, exponential distribution and power-law distribution; Subsequently, determine the topological structure of initial network, such as stelliform connection topology configuration, full-mesh topological structure, carry out the structure of microblog users relational network evolutionary model on this basis;
2) in network evolution process, when there being new node to add network, by random increase mechanism and preferential attachment mechanism, carry out new node interpolation, then by random connection mechanism and Opposite direction connection mechanism, node connection is carried out to the network after interpolation new node, form network evolution model.
This step specifically comprises:
2.1) random increase mechanism:
In each time interval, increase a new node in initialization network model, and choose m in initialization network model
1individual node connects, wherein, and m
1≤ m
0;
2.2) preferential attachment mechanism:
Obtain the probability Π of each node in initialization network model
i, Π
iexpression formula be
wherein k
jfor the degree of a jth node in initial network model, a
jfor the Attraction Degree of an initial network model jth node; According to the probability Π of each node
i, choose m from big to small
1node in individual initialization network model, sets up the directed connection being pointed to newly added node by selected node;
2.3) random connection mechanism:
M in random selecting initial network model
2individual node as terminal, according to the probability Π of all the other nodes in initial network model
i, choose m from big to small
2individual node as start node, and with selected m
2individual terminal sets up m successively
2bar directed connection; Wherein, m
2≤ m
0;
2.4) Opposite direction connection mechanism:
Predetermined probabilities q, according to default probability q, Opposite direction connection is added in the unidirectional connection newly-built to every bar.
Network evolution generates node and adopts random growth, preferential attachment, random connection and Opposite direction connection four kinds of mechanism, the feature that random increase mechanism constantly increases for describing microblog users relational network scale; Preferential attachment mechanism is more easily subject to the fact of other users concern for portraying the more users of bean vermicelli; Random situation of adding perpetual object is there is in random connection mechanism for representing microblog users; Opposite direction connection mechanism adds for illustration of being concerned user the behavior oppositely paid close attention to; Specifically comprise the following steps:
In A, the evolutionary model that proposes in the present invention, if party A-subscriber has paid close attention to party B-subscriber, show that the former can see the blog article that the latter upgrades in time, so just established one between user A and B and point to the connection of A from B.If user B has also paid close attention to user A, a nonoriented edge between two users, will be set up;
B, initial network set: first, set the nodes m of initial network as required
0, and give corresponding Attraction Degree to each node, Attraction Degree here may meet different distributions, is such as uniformly distributed, exponential distribution and power-law distribution etc.; Subsequently, determine the topological structure of initial network, such as star-like, full-mesh etc., carries out the structure of microblog users relational network evolutionary model on this basis;
The growth of C, network size: in whole evolutionary process, network size is ascending to be increased at random, and gives an Attraction Degree to each node newly adding network;
D, there is choosing of node: when a new node adds network, need to select already present m in network
1individual node sets up new connection; Choosing of connection establishment process interior joint, depends on degree and the Attraction Degree product of this node;
E, exist between node and set up random connection: random selecting node is as the start node of newly-built connection, and choosing of terminal is determined by the degree of this node and Attraction Degree product, sets up by the directed connection of start node sensing terminal on this basis;
The foundation of F, Opposite direction connection: consider to there is situation about oppositely paying close attention in true microblog users relational network, to the node newly connected to interpolation Opposite direction connection.
Consider the degree k of node i
iand Attraction Degree a
ito the importance of structure microblog users relational network, in the present invention, with the product of the degree of node and Attraction Degree
as basis for estimation when setting up new connection, namely degree or the larger node of Attraction Degree larger by the possibility selecting to connect; One is newly added to the node of network, even if its node degree is very little, as long as have larger Attraction Degree, this node also can receive the concern of a lot of microblog users within a short period of time.
In the present invention when a new node adds network, in network, add new directed connection; Setting up in random connection procedure, the start node random selecting on limit, terminal is then with probability
select; To each newly-established connection, all set up Opposite direction connection with probability q.
Specific algorithm flow process of the present invention as depicted in figs. 1 and 2.
Fig. 1 carries out initialization to network adjacent matrix A, and after initialization, A is a m
0rank square formation, initial network is a full-mesh network.In initialization procedure, set the Attraction Degree meeting certain distribution to each node, each connection in initial network is all two-way.
Fig. 2 indicates the concrete evolutionary process of evolutionary model.In evolutionary process, when a new node joins network, with already present m in network
1individual node sets up new connection.The process of connection establishment considers the effect of node and node Attraction Degree simultaneously, and therefore the node be selected for connecting depends on probability
owing to there is situation about paying close attention to being concerned, the direction of newly-built connection is point to newly added node by existing node, and direction here refers to the flow direction of information.In forming process, also there is the situation of adding and oppositely paying close attention in microblog users relational network, the present invention's hypothesis all adds Opposite direction connection with probability q for each new connection.
In evolutionary process, there is random situation of adding connection between microblog users, suppose newly to establish m
2bar connects at random.The one end connected is chosen at random in a network, and the other end is with probability
choose, the direction of connection points to the former by the latter.Be simultaneously that each newly connects interpolation Opposite direction connection with probability q again.
From Fig. 1, Fig. 2, the core of evolution algorithmic is preferential attachment mechanism and random connection mechanism, and namely in microblog users relational network evolutionary process, when a new node adds network, the probability choosing the node that to connect with this node is
when setting up m at random
2when bar connects, random selecting principle is followed in the one end on limit, and the probability that the other end is chosen is
Beneficial effect of the present invention is as follows:
First the present invention carries out initialization to network, random growth, preferential attachment, random connection and Opposite direction connection mechanism is adopted to complete the evolutionary process of whole network subsequently, thus make the present invention farthest can reflect the forming process of true microblog users relational network, portray the various statistical natures that live network has as much as possible.
At microblog users relational network evolution generation phase, each time step has a node to join network, shows with this characteristic that network size increases at random; Mutually adding in the process paid close attention to, including and give priority to and pay close attention to two kinds of situations at random; The interpolation oppositely paid close attention to then is carried out with certain probability.The present invention adopts simple rule to construct to have the microblog users relational network of complex characteristics, is convenient to realize in the form of software, can be used in the research of the aspects such as the analysis of social media, public sentiment transmission controe and network communication efficiency.
The present invention has carried out the optimal design of efficiency while raising practicality, avoid the appearance repeating establishment of connection and isolated node between two nodes, and the scale of the generating network that develops is unrestricted, can be used in requiring larger research environment to network size.
Present invention incorporates the feature of WS small-world network generating algorithm and BA scales-free network generating algorithm, the topological characteristic of true microblog users relational network can be reproduced more objectively, structure is simple, Evolution Rates is fast, complexity is lower, better portable, be suitable for portraying various real microblog users relational network.
Claims (4)
1. a microblog users relational network evolutionary model building method for science Network Based, is characterized in that, comprise the following steps:
1) setting nodes is as required m
0network model, all give Attraction Degree to each node, and determine the topological structure of initial network, random selecting node, makes this node and all the other m
0-1 node is all connected, forms initialization network model;
2) in network evolution process, when there being new node to add network, by random increase mechanism and preferential attachment mechanism, carry out new node interpolation, then by random connection mechanism and Opposite direction connection mechanism, node connection is carried out to the network after interpolation new node, form network evolution model.
2. the microblog users relational network evolutionary model building method of science Network Based according to claim 1, it is characterized in that, described step 2 specifically comprises:
2.1) random increase mechanism:
In each time interval, increase a new node in initialization network model, and choose m in initialization network model
1individual node connects, wherein, and m
1≤ m
0;
2.2) preferential attachment mechanism:
Obtain the probability Π of each node in initialization network model
i, Π
iexpression formula be
wherein k
jfor the degree of a jth node in initial network model, a
jfor the Attraction Degree of an initial network model jth node; According to the probability Π of each node
i, choose m from big to small
1node in individual initialization network model, sets up the directed connection being pointed to newly added node by selected node;
2.3) random connection mechanism:
M in random selecting initial network model
2individual node as terminal, according to the probability Π of all the other nodes in initial network model
i, choose m from big to small
2individual node as start node, and with selected m
2individual terminal sets up m successively
2bar directed connection; Wherein, m
2≤ m
0;
2.4) Opposite direction connection mechanism:
Predetermined probabilities q, according to default probability q, Opposite direction connection is added in the unidirectional connection newly-built to every bar.
3. according to the microblog users relational network evolutionary model building method of the science Network Based in claim 1, it is characterized in that, described Attraction Degree is arranged according to network model distribution, the distribution of described network model comprise be uniformly distributed, exponential distribution and power-law distribution.
4. according to the microblog users relational network evolutionary model building method of the science Network Based in claim 1, it is characterized in that, the topological structure of described initial network comprises stelliform connection topology configuration and full-mesh topological structure.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107918610A (en) * | 2016-10-09 | 2018-04-17 | 郑州大学 | A kind of microblogging propagation model towards Time Perception |
| CN110362818A (en) * | 2019-06-06 | 2019-10-22 | 中国科学院信息工程研究所 | Microblogging rumour detection method and system based on customer relationship structure feature |
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| CN1930545A (en) * | 2003-10-20 | 2007-03-14 | 特里诺尔公司 | Backward and forward non-normalized link weight analysis method, system, and computer program product |
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| 王亚奇等: "rumor spreading model with trust mechanism in complex social networks", 《COMMUNICATIONS IN THEORETICAL PHYSICS》 * |
| 王亚奇等: "一种无线传感器网络簇间拓扑演化模型及其免疫研究", 《物理学报》 * |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107918610A (en) * | 2016-10-09 | 2018-04-17 | 郑州大学 | A kind of microblogging propagation model towards Time Perception |
| CN110362818A (en) * | 2019-06-06 | 2019-10-22 | 中国科学院信息工程研究所 | Microblogging rumour detection method and system based on customer relationship structure feature |
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