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Two-stage memetic based social network influence maximizing method

A technology of maximizing influence and social network, applied in the complex network field, can solve problems such as not applicable to large-scale social networks, and achieve the effect of narrowing the search scope

Inactive Publication Date: 2016-08-17
XIDIAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, experiments have shown that the algorithm is still not suitable for large-scale social networks

Method used

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  • Two-stage memetic based social network influence maximizing method
  • Two-stage memetic based social network influence maximizing method
  • Two-stage memetic based social network influence maximizing method

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Experimental program
Comparison scheme
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Embodiment Construction

[0039] refer to figure 1 The realization steps of the present invention are as follows:

[0040] Step 1, input the target network: G=(V,E)

[0041] Among them, G represents the input social network, V represents the node set of the network, and E represents the edge set of the network.

[0042] Step 2, network clustering.

[0043] Use the BGLL algorithm proposed by Blondel et al. in "Fast unfolding of communities in large networks" ("Journal of Statistical Mechanics: Theory and Experiment", 2008) to divide the input social network into communities. The implementation steps are as follows:

[0044] (21) Treat each node in the network as a community, and then move each node from their original community to the community where the neighbor node that can make the modularity gain the largest. This process continues until the modularity gain cannot be increased by moving any point.

[0045] (22) Treat each community obtained in the previous step as a node, so as to obtain a new ...

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Abstract

The present invention discloses a two-stage memetic based social network influence maximizing method. The implementing steps of the method comprise: (1) network clustering; (2) candidate nodes selection; and (3) finding out an important node set capable of maximizing the social network influence in the candidate nodes. The step (3) comprises: 1) determining an objective function; 2) constructing an initial solution population, and initializing individuals in the solution population by using a similarity based degree centrality method; 3) sequentially carrying out selection, and crossover and mutation operations on the individuals in the solution population, so as to obtain offspring individuals; 4) updating the solution population by using the offspring individuals; 5) locally searching the being updated solution population; and 6) determining whether the update is terminated, and if the number of iterations satisfies the preset number, performing the step 7), otherwise, returning to the step 3). The method disclosed by the present invention can effectively find out the initial important node set capable of maximizing the influence range in massive social networks, and effectively solves the problem of social network influence maximization.

Description

technical field [0001] The invention belongs to the field of complex networks, and relates to a social network influence maximization method, in particular to a social network influence maximization method based on a two-stage memetic, which can be used to discover important node sets in a social network. Background technique [0002] With the rapid development of Web2.0 technology, online social networks are rapidly popularized, and online social network platforms such as Facebook and Twitter are getting more and more attention. With the growth of the user scale of these online social network platforms, they have become the product promotion and information dissemination platforms chosen by many new companies. On these platforms, users are allowed to build their own social circles and share information with their friends. This makes the spread of influence easier. [0003] Word-of-mouth marketing is a very effective strategy for online social network marketing. Its purpos...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/00G06N3/12G06K9/62
CPCG06N3/126G06Q50/01G06F18/2321
Inventor 公茂果宋超马晶晶段超马文萍王善峰马里佳沈波
Owner XIDIAN UNIV
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