A method and system for analyzing the evolution of a dynamic social network community

A social network and analysis method technology, applied in data processing applications, instruments, calculations, etc., can solve the problems of core node type differentiation, failure to make full use of network topology information, etc., and achieve high accuracy and efficiency

Active Publication Date: 2021-06-25
CHINA UNIV OF MINING & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] In view of the above analysis, the embodiment of the present invention aims to provide a dynamic social network community evolution analysis method and its system to solve the problems that the prior art fails to make full use of network topology information and does not distinguish the types of core nodes The problem

Method used

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  • A method and system for analyzing the evolution of a dynamic social network community
  • A method and system for analyzing the evolution of a dynamic social network community
  • A method and system for analyzing the evolution of a dynamic social network community

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Embodiment 1

[0086] A specific embodiment of the present invention discloses a method for analyzing the evolution of a dynamic social network community, such as figure 1 shown, including the following steps:

[0087] S1. For a given dynamic social network, starting from the first time slice, divide the community structure corresponding to the time slice network for each time slice;

[0088] S2. Calculate the superspreader set of each time slice network and the superblocker set of each community corresponding to the time slice network according to the community structure division results;

[0089] S3. For the above-mentioned superspreader set, determine the evolution event 1 type of each community; the possible types of the evolution event 1 include generation, merger and expansion events;

[0090] S4. For the above superblocker set, determine the evolution event 2 type of each community; the possible types of the evolution event 2 include disappearance, splitting and shrinking events.

...

Embodiment 2

[0093] Optimizing on the basis of Example 1, such as figure 2 As shown, step S1 can be further refined into the following steps:

[0094] S11. For a given dynamic social network, starting from the first time slice, obtain the neighbor relationship between each node in each time slice network;

[0095] S12. According to the neighbor relationship above, divide the community structure corresponding to each time slice network through the QCA algorithm.

[0096] The QCA algorithm is a fast adaptive dynamic community discovery algorithm based on modularity. It formulates different community structure update strategies for each network change, including node addition, node deletion, edge addition, and edge deletion. By maximizing modularity To determine the community affiliation of incremental nodes.

[0097] Preferably, as image 3 As shown, step S2 can be further refined into the following steps:

[0098] S21. Obtain the superspreader set of each time slice network through the...

Embodiment 3

[0145] Another specific embodiment of the present invention discloses a dynamic social network community evolution analysis system, which uses the method described in Embodiment 1 to perform evolution analysis. Specifically, such as Figure 6 As shown, the dynamic social network community evolution analysis system includes a community division module, a superspreader set calculation module, a superblocker set calculation module, a superspreader-based evolution event analysis module, and a superblocker-based evolution event analysis module. Among them, the output of the community division module is connected to the input of the superspreader set calculation module, the superblocker set calculation module, the superspreader-based evolution event analysis module, and the superblocker-based evolution event analysis module. The output end of the superspreader set calculation module is connected to the input end of the superspreader-based evolution event analysis module, and the out...

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Abstract

The invention relates to a dynamic social network community evolution analysis method and system thereof, belonging to the technical field of network identification, and solves the problems that the prior art fails to make full use of network topology information and does not distinguish the types of core nodes. The method comprises the following steps: for a given dynamic social network, starting from the first time slice, dividing the community structure corresponding to the time slice network for each time slice; The superspreader set and the superblocker set of each community corresponding to the time slice network; for the superspreader set, determine the evolution event 1 type of each community, that is, generation, merger and expansion events; for the superblocker set, determine the evolution event 2 of each community Types, namely disappearance, splitting, and shrinking events. The invention utilizes the characteristics of superspreader's strong dissemination and superblocker's ability to destroy connectivity, and analyzes dynamic social network community evolution events according to the changes of the two types of node sets, and the evolution event recognition accuracy and efficiency are high.

Description

technical field [0001] The invention relates to the technical field of network identification, in particular to a dynamic social network community evolution analysis method and system thereof. Background technique [0002] Generally, community structures are hidden in complex social networks, users in the same community are closely connected, while users in different communities are relatively sparsely connected. Realistic social networks will change frequently and continuously over time, so only studying the static characteristics of social networks is not enough to characterize its authenticity. At present, researchers are paying more and more attention to the evolution of dynamic social networks, which are used in many fields have a wide range of applications. For example, for a disease transmission network, tracking the community changes of infected patients helps to find the transmission path of the disease, so as to find effective measures to control the spread of the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 王志晓徐志鸥席景科袁冠何婧
Owner CHINA UNIV OF MINING & TECH
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