A microblog forward influence ranking method based on a neural network

Abstract

The invention belongs to the technical field of network science, and discloses a microblog forward influence ranking method based on a neural network. The microblog forward influence ranking method based on the neural network comprises the step of carrying out the forward influence analysis and ranking on the text content issued by microblogs through the neural network; collecting the microblog release text data and the user basic data; sorting, summarizing and analyzing the collected data by using the neural network model and preset parameters; and outputting the ranking results. The neural network is a BP neural network having three or more layers of multi-layer neural networks. The microblog forward influence ranking method based on the neural network avoids the fact that microblog publishers do not select means to increase likes to be translated and spend rumor release, guides the microblog publishers to pay attention to release content, is beneficial to guiding negative sounds, and forms a good network public opinion environment.

Description

technical field [0001] The invention belongs to the field of network science and technology, in particular to a method for ranking the positive influence of microblogs based on neural networks Background technique [0002] At present, the ranking method adopted by Weibo is based on quantitative indicators such as interaction, forwarding, and likes, and does not involve the analysis of Weibo content, and there is no ranking method for the positive influence of Weibo content. [0003] In summary, the problems in the prior art are: [0004] (1) Does not involve the ranking of the positive influence of Weibo; lack of analysis of Weibo content; [0005] (2) Ranking quantitative indicators are easy to be manipulated; [0006] (3) In the prior art, the abnormal content released by Weibo cannot be detected in time, resulting in the wanton dissemination of bad content and causing network "pollution". [0007] The difficulty and significance of solving the above technical problems:...

AI Technical Summary

Problems solved by technology

[0004] (1) Does not involve the ranking of the positive influence of Weibo; lack of analysis of Weibo content;

[0005] (2) Ranking quantitative indicators are easy to be manipulated;

[0006] (3) In the existing technology, the abnormal content published by Weibo cannot be detected in time, resulting in the wanton dissemination of bad content and causing network "pollution"

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