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Influential communicator recognizing and quantifying method in online social network

A social network and communicator technology, applied in the field of identification and quantification of influential communicators in online social networks, it can solve the problem of high time complexity and achieve high efficiency.

Inactive Publication Date: 2018-04-20
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] In the existing technology, the ordinary greedy algorithm (NGA algorithm) can achieve the purpose of identifying and quantifying influential communicators in social networks, but the time complexity is very high

Method used

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  • Influential communicator recognizing and quantifying method in online social network
  • Influential communicator recognizing and quantifying method in online social network
  • Influential communicator recognizing and quantifying method in online social network

Examples

Experimental program
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Embodiment 1

[0037] This embodiment uses a computer to generate a random network whose degree sequence is Poisson distribution through a given node degree sequence. The node size N of the graph described in this embodiment is selected from 18 types, starting from 10,000, m is set to 32.9, and the number M of control vertex group vertices is 10. First, generate a network with a size of N (10,000) for experimentation, then multiply N by a fixed constant 1.3, continue to generate a network with a size of N and use NGA (Natural Greedy Algorithm) and PBGA algorithm respectively.

[0038] The specific implementation steps of PBGA are as follows:

[0039] S.1 Initialize the active node set T as an empty set;

[0040] S.2 Select a node i from the graph as a disseminator, and join the set T;

[0041] S.3 According to the preset probability value v(β c ≤v≤1), edge percolation processing is performed on the selected nodes, the β c is the percolation threshold predetermined according t...

Embodiment 2

[0047] In this embodiment, the structural data of the topological network is acquired from the social network information database. Select eleven actual networks, CA-GrQc, CA-HepTh, Macau Weibo, EmailEnron, NOLA Facebook, DBLP, Delicous, QQ and LiveJournal, corresponding to Figure 5 The abscissa of the 11 points near the circle dotted line and the square dotted line is the scale of these networks. Still control the vertex number M of the vertex group to 10, and set m to 32.9. NGA and PBGA algorithms are used in these eleven networks to operate respectively.

[0048] The specific implementation steps of PBGA are as follows:

[0049] S.1 Initialize the active node set T as an empty set;

[0050] S.2 Select a node i from the network topology graph as the disseminator, and join the set T;

[0051] S.3 According to the preset probability value v(β c ≤v≤1), edge percolation processing is performed on the selected nodes, the β c is the percolation threshold predet...

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Abstract

The invention belongs to the field of information, and particularly relates to an influential communicator recognizing and quantifying method in an online social network. The social network is abstracted as a graph G (V, E) on the basis of an SIR family communication model, wherein V represents the set of nodes, E represents the set of edges, and each edge indicates the relationship between the nodes. The communication capacity S of all the nodes in the graph G (V, E) is calculated by using a greedy algorithm based on the percolation theory, and the size of the communication capacity S of allthe nodes is ordered so that the top M vertexes of the highest communication capacity are found. The beneficial effects of the method are that the global network communication influence is measured through the local network structure so that the time complexity of the algorithm can be reduced.

Description

technical field [0001] The invention belongs to the field of information, in particular to a method for identifying and quantifying influential communicators in an online social network. Background technique [0002] Modern online social networking platforms are gradually replacing traditional media with their powerful communication and communication functions, becoming an important part of modern people's daily life. A common characteristic of these social networks is their enormous size. The explosive dissemination of some information will have an impact on the entire social network, which is also the theoretical basis for some marketing methods. [0003] Vertex propagation capability refers to the expected value of the number of other vertices that a vertex can ultimately affect if it propagates a message. At present, the field believes that the measurement of vertex propagation influence needs to obtain the global information of the network, and the most popular measur...

Claims

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Application Information

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IPC IPC(8): G06Q50/00G06F17/30
CPCG06Q50/01G06F16/95
Inventor 胡延庆贾寒孙嘉辰谢家荣刘荣
Owner SUN YAT SEN UNIV
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