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Method for discovering key person in a dynamic large-scale social network

A key person and social network technology, applied in the field of key person discovery, can solve problems such as the dynamics of social networks and the nature of big data, and the high time complexity of algorithms

Active Publication Date: 2017-05-31
BEIHANG UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The above work on social network analysis and key person discovery does not take into account the dynamics and big data properties of real social networks, and the global algorithm has a high time complexity

Method used

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  • Method for discovering key person in a dynamic large-scale social network
  • Method for discovering key person in a dynamic large-scale social network
  • Method for discovering key person in a dynamic large-scale social network

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Embodiment Construction

[0028] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0029] The present invention proposes a method for discovering key figures in a dynamic large-scale social network. key person. The dynamic large-scale social network refers to a complex network in real life, such as a social network composed of all users of Sina Weibo. The network data scale is huge, the structure is extremely complex, and the relationship between people is changing dynamically. The aforementioned key person refers to a person who can play a key role in the network. For example, a big V on Sina Weibo can influence his fans and play a key role in disseminating information.

[0030]The method proposed in the present invention for finding key figures in a dynamic large-scale social network mainly includes four processes: (1) node label and parameter selection; (2) local network extraction and mutual influence calculation betwee...

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Abstract

The invention discloses a method for discovering key person in a dynamic large-scale social network, which belongs to the field of data mining and social network analysis. The method first performs node labeling and parameter K selection, and then calculates the mutual influence between the nodes in a certain localized network. The importance index of the single node is calculated and the key person is found according to the task type. The method for discovering key person in a dynamic large-scale social network puts forward a concept of universal influence, and gives a formula of calculating the mutual influence between the nodes in a certain localized network and the importance index, and has advantages in the large-scale dynamic social network. According to the difference of the task type, the method can have different result processing strategies, and can adjust the parameter K to balance the time complexity and accuracy.

Description

technical field [0001] The invention relates to a method for calculating node importance indexes in a complex network and discovering key figures in a dynamic large-scale social network, and belongs to the fields of data mining and social network analysis. Background technique [0002] In recent years, more and more people have begun to use online social networking applications such as Weibo, Twitter, and Facebook, resulting in an explosive growth in the total amount of social network data; at the same time, the rapid growth of the network scale has led to a dynamic network structure. Variety. Users can exchange and share information on these social network platforms, and different users have different influences, so it is of practical significance to identify key figures in social networks. [0003] In the initial stage of research, traditional centrality indicators are widely used. Among them, the simplest is the degree centrality: only according to the number of neighbo...

Claims

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Application Information

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IPC IPC(8): H04L12/24
CPCH04L41/145
Inventor 牛建伟杨海峰
Owner BEIHANG UNIV
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