Method and system for maximizing social network influence based on node coverage

A coverage and social network technology, applied in the field of social network influence maximization methods and systems, can solve the problems of inaccurate node centrality evaluation, poor network adaptability, overlapping node influence ranges, etc., and achieve effective node centrality indicators, The effect of good adaptability

Active Publication Date: 2021-02-02
CHINA UNIV OF MINING & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] In view of the above analysis, the present invention aims to provide a method and system for maximizing social network influence based on node coverage, which solves the problems of overlapping node influence ranges, inaccurate evaluation of node centrality, and network The problem of poor adaptability

Method used

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  • Method and system for maximizing social network influence based on node coverage
  • Method and system for maximizing social network influence based on node coverage
  • Method and system for maximizing social network influence based on node coverage

Examples

Experimental program
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Embodiment 1

[0060] Such as figure 1 As shown, this embodiment provides a method for maximizing social network influence based on node coverage, including the following steps:

[0061] Step S1. Determine the coverage gain value of each node in a given social network according to the neighbor relationship of each node in the social network;

[0062] Step S2, selecting a seed node according to the coverage gain value of the above nodes to obtain a set of seed nodes;

[0063] Step S3, using the above seed node set to determine the social network influence maximization node set.

[0064] Compared with the existing technology, the social network influence maximization method based on node coverage provided by this embodiment solves the problem that the seed nodes selected by the existing method are too concentrated, resulting in overlap of node influence ranges, and adopts a more effective node The centrality index can accurately and effectively select the most influential nodes, and has good...

Embodiment 2

[0085] Such as figure 2 As shown, this example also provides a social network influence maximization system based on node coverage, including: a node coverage gain value calculation module, a seed node selection module, and an influence maximization node set generation module;

[0086] The node coverage gain value calculation module is used to determine the coverage gain value of each node in the social network according to the neighbor relationship of each node in the given social network;

[0087] The seed node selection module is connected with the node coverage gain value calculation module, and is used to select the seed node according to the coverage gain value of the node to obtain the seed node set;

[0088] The influence maximization node set generating module is used to determine the social network influence maximization node set by using the seed node set obtained by the above seed node selection module.

[0089] Compared with the existing technology, the social n...

Embodiment 3

[0108] This embodiment relates to the Book network, based on the above-mentioned node coverage-based influence maximization method to identify the network's influence maximization node set, wherein the information of the network Book is shown in Table 1, the network contains 105 nodes and 441 edges (In a social network, a node represents a person, and an edge represents a connection between people).

[0109] Table 1: Network Book Details

[0110] The internet node side book 105 441

[0111] Using the social network influence maximization method based on node coverage to identify the influence maximization node set in the Book network specifically includes the following steps:

[0112]1) Preliminarily calculate the initial coverage gain value of each node in the Book network (that is, the degree value of the node) by using the node neighbor relationship. Some calculation results are shown in Table 2

[0113] Table 2: Initial coverage gain values ​​of...

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Abstract

The invention relates to a social network influence maximization method and a system based on node coverage, and belongs to the technical field of network analysis. Problems of overlapping the influence range of nodes in the prior art, inaccurate evaluation of the centrality of the nodes, and poor adaptability to networks of different structures are solved. The method comprises the following steps: determining the coverage gain value of each node in the social network according to the neighbor relationship of each node in the given social network; selecting a seed node according to the coverage gain value of the node to obtain a seed node set; determining the social network influence maximization node set by using the seed node set. Through more effective node centrality indicators, the most influential nodes are accurately and effectively selected, the problem that the selected seed nodes are too concentrated to cause the overlapping influences of the nodes is solved, and good adaptability is achieved for networks of different structures.

Description

technical field [0001] The invention relates to the technical field of network analysis, in particular to a method and system for maximizing social network influence based on node coverage. Background technique [0002] Influence maximization is an important content of social network analysis. Its goal is to find a set of seed nodes in the social network. Under a given propagation model, the influence of these nodes will be the largest. With the development of the Internet and big data, the scale of the network is showing a trend of increasing rapidly, and the maximization of influence is widely used in marketing strategies, targeted advertising, public opinion prediction and control. [0003] There are two main types of existing social network influence maximization methods: one is based on propagation, and the other is based on topology. The propagation-based method needs to traverse the entire network each time to select a node, and it takes too long to run in a large-sc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 王志晓席景科刘佰龙赵莹王荣存高菊远
Owner CHINA UNIV OF MINING & TECH
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