An Evolutionary Analysis Method for Association Networks in Forums

Abstract

The invention provides a method for analyzing the evolution of associated networks in forums, 1. Reasonable time division and segment extraction; 2. Measurement parameters for measuring community evolution; 3. Longest common subsequence algorithm for solving public nodes in groups; 4. , Discovery of cut points in community network graph based on DFS algorithm. The present invention is applicable to different applications, networks of different scales, and networks of different types. It can be used as long as it can be converted into an undirected graph and follows the same principles. Not only can it be used for the visualization of community network discovery, but also it can analyze the changes of the extracted network over time. Through the analysis of multiple posts, it is found that the evolution process of different posts is also different. For posts with unattractive and boring content, they only have a certain number of replies in the initial stage of posting, and the number of generated communities is relatively small. Important There are also relatively few active nodes. And for those attractive posts, it will last for a long time and the number of communities is large.

Description

technical field [0001] The invention relates to an evolution analysis method of an associated network in a forum, and belongs to the technical field of network evolution analysis methods. Background technique [0002] In the process of community evolution, the community level will continue to change, and a single level of community discovery is difficult to ensure a reasonable community structure, so it may not be able to accurately discover the community evolution process. Not only that, but the existing criteria for judging the type of community evolution are difficult to meet the complexity of community changes. In the existing community discovery methods, there are some problems as follows: [0003] (1) When analyzing the network community structure at different times, in order to compare the change process of the community under the same condition, a fixed parameter standard is used for community extraction. However, during the evolution of the community, the cohesion...

AI Technical Summary

Problems solved by technology

However, during the evolution of the community, the cohesion and strength of the community will continue to change, and the fixed parameter standard is difficult to ensure a reasonable community structure and accurately discover the evolution process of the community.

[0004] (2) The evolution type division of the community is not reasonable enough

In many cases, community changes are complex, and it is difficult to accurately describe them by increasing, reducing, merging, and decomposing.

In addition, the definition of the evolution type of the community is too absolute, and the influence of the changing part and the static part in the community on the change type of the community is not fully considered

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