Method for recognizing social network sock puppet model based on frequency sub-tree

A social network, frequent technology, applied in the field of social network vest recognition model, can solve the problem of not being able to depend on the same time, and achieve the effect of effective recognition

Inactive Publication Date: 2017-04-26
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] (3) Any one component cannot depend

Method used

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  • Method for recognizing social network sock puppet model based on frequency sub-tree
  • Method for recognizing social network sock puppet model based on frequency sub-tree
  • Method for recognizing social network sock puppet model based on frequency sub-tree

Examples

Experimental program
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Embodiment Construction

[0049] Specific implementation steps:

[0050] Step 1: Extract the Weibo content of some users in Sina Weibo. For example: (taking the first ten microblogs of two users as an example) User 1:

[0051] Yes, when I was a child, I picked this one and ate it. There is also a black one, which is sweeter, but the teeth turn black after eating it. [嘻嘻] / / @雄镇李: When I was a child, there were many ditches on the roadside and in the fields, so I don’t have to say it tastes good [Glutton]

[0052] you're back? I'm going to Hong Kong tomorrow, isn't the temperature in Hong Kong still high? How many clothes do I need to wear? [hehe]

[0053] Student Xiaoqi, why can't I see you in the circle of WeChat friends? / / @陈琪-fairy:@nanahu1997

[0054] How to describe it, papa bear, do you want to lie so close to the ground? . @Creative Advertising Highlights

[0055] In today's information society, if the traditional business model has not been innovated and upgraded, there will be nowhere ...

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Abstract

The invention relates to a method for recognizing a social network sock puppet model based on a frequency sub-tree. The method comprises the following steps: 1) acquiring blog text data; 2) pre-processing the data; 3) utilizing dependency grammar analysis software to perform dependency grammar analysis on the blog text, and acquiring a grammar analysis result for each blog post; 4) adopting a Pre-Order-String method for expressing a dependency grammar tree acquired in the step 3); 5) utilizing the method adopted in the step 4) to acquire the analysis result for each text in someone's blog list; and 6) analyzing two accounts, to be subjected to judgment for sock puppet relation, according to the steps 1)-5), thereby acquiring a frequency dependency grammar tree of two sock puppet accounts. According to the method for recognizing the social network sock puppet model based on the frequency sub-tree, provided by the invention, after a large amount of data training, the method can be applied to the management of the social network for the network safety and the network crime trace of the government, and the sock puppet account can be quickly and effectively recognized.

Description

technical field [0001] The invention relates to a frequent subtree-based social network waistcoat recognition model method, which is applied to the text author relationship identification in the social network and belongs to the technical field of data mining. Background technique [0002] At present, with the rapid development of science and technology, especially the development of Internet technology, the total number of global Internet users has exceeded 3 billion, and 2.31 billion social media users. In the "Monitoring Report on the Number of Monthly Active Users of Mobile Internet in China in January 2016" released by CCID Consulting, the monthly active users of WeChat, QQ, and Sina Weibo ranked among the top three. In social networks, it is very common for the same person to have multiple accounts. Someone will register a Weibo ID, which is often used or logged in as the primary ID. Now many netizens are not satisfied with one Weibo ID and will register other Weibo I...

Claims

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Application Information

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IPC IPC(8): G06F17/27
CPCG06F40/211G06F2216/03
Inventor 段大高高飒韩忠明
Owner BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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