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A social network influence maximization method based on community structure

A technology of social network and influence, applied in the field of social network, it can solve the problems of sparse community connection, not considering the network structure, etc., so as to improve the accuracy and operation efficiency, and solve the problem of maximizing the influence of social network.

Active Publication Date: 2022-02-08
SHANDONG UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of the current work does not take into account the actual structure of the network. Each network has the characteristics of a community structure, that is, the community is closely connected and the connections between communities are sparse.

Method used

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  • A social network influence maximization method based on community structure
  • A social network influence maximization method based on community structure
  • A social network influence maximization method based on community structure

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0088] 1. Dataset and Experimental Setup

[0089] In this example, four publicly available datasets HepTh dataset, Brightkite dataset, Epinions dataset and Amazon dataset from SNAP of different scales are used. The HepTh dataset comes from a high-energy physics theory collaborator network and is an undirected graph. The Brightkite dataset is a location-based social network, which is an undirected graph. The Epinions data set comes from the trust network, which is a link relationship formed by members of the Epinions website choosing partial trust to comment, so it is a directed graph. The Amazon data set comes from the Amazon purchase website. If two products in the website are often purchased together, there will be a link relationship, so there is also a directed graph. The static structural feature statistics of these four datasets are shown in Table 1.

[0090] Table 1: Statistics of static structural features of experimental data

[0091]

[0092] The threshold val...

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PUM

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Abstract

The invention discloses a method for maximizing the influence of a social network based on a community structure. The specific process of the method is as follows: (1) Divide the community to form a candidate node set, and identify the core nodes and nodes in the network by dividing the network. (2) Select nodes heuristically, and for each node in the candidate node set, verify the potential influence through the degree of the node, the community size, the number of connected communities and the influence weight, so as to inspire (3) Implement the greedy algorithm, and use the greedy algorithm to select the node with the largest marginal income to join the seed set. The present invention further improves the accuracy and operating efficiency of digging initial seed nodes by analyzing the role of community structure in influence propagation, and effectively solves the problem of social network influence maximization.

Description

technical field [0001] The invention relates to the field of social networks, in particular to a method for maximizing social network influence based on community structure. Background technique [0002] In recent years, with the rise of social networks, more and more social platforms such as Facebook, Twitter and Google+ have attracted widespread attention. As the carriers of social networks, these platforms enable various information to be disseminated on social networks. How to maximize the dissemination of this information through these social platforms and allow more users to accept this information is called the "problem of maximizing influence". The problem of social network influence maximization is a hot issue in social network research, and has great application value in the fields of marketing, disease spread and rumor control. [0003] The social network influence maximization problem is how to select Top-K seed nodes for propagation, so as to maximize the fina...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 仇丽青于金凤范鑫
Owner SHANDONG UNIV OF SCI & TECH
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