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Microblog advertisement user detection method

A detection method and user technology, applied in the field of social network security, can solve problems such as reducing the efficiency of real-time search engines on social networks, and achieve the effects of good comprehensive performance, high accuracy and regression

Inactive Publication Date: 2013-12-18
SHANGHAI JIAO TONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

This kind of behavior can be used by advertisers to hype their own websites. At present, many users are deeply harassed by advertisers, and advertisers also reduce the efficiency of social network real-time search engines.

Method used

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  • Microblog advertisement user detection method
  • Microblog advertisement user detection method
  • Microblog advertisement user detection method

Examples

Experimental program
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Embodiment Construction

[0035] Such as figure 1 As shown, the embodiment provides a method for detecting abnormal Weibo users, including:

[0036] Step 1 collects microblog user data and performs manual category identification;

[0037] Step 2 performs feature extraction on the user in the step 2, and selects a feature attribute set;

[0038] In step 3, according to the user category identified in step 1 and the feature attribute set extracted in step 2, the data mining classification algorithm is used for model training to obtain a user discrimination model;

[0039] Step 4 uses the user discrimination model trained in step 3 to predict users of microblog advertisements.

[0040] Taking Sina Weibo as an example, for the above four steps, the specific implementation steps are described as follows:

[0041] First, collect Weibo user data and perform manual category identification.

[0042] Its specific process is as figure 2 As shown, the description is as follows:

[0043] User data is collect...

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Abstract

The invention discloses a Microblog advertisement user detection method. The method includes the steps that user information is collected, and classifying identification is added for each user; feature extraction is performed on the acquired used information, and content of advertisement users and common users and a feature attribute set of action are obtained on the basis of a data mining method; according to the feature attribute set with the classification identification, model training is performed, and an advertisement user discrimination model is obtained. Due to the fact that all features of the Microblog users are comprehensively analyzed, accuracy and regression of the trained discrimination model are high, comprehensive performance is good, and the defect that a detection tool built in Sina is not flexible on the advertisement users is overcome.

Description

technical field [0001] The invention relates to the field of social network security, in particular to a method for detecting microblog advertisement users. Background technique [0002] In China, online social networking has become a major platform where people gather information and meet like-minded people. Sina Weibo is called "Twitter" because of its similarity to Twitter. However, from the perspective of user usage habits and different cultures, what we call Weibo and Twitter are different. According to the research of Hewlett-Packard Labs, people prefer to forward information on Weibo rather than publish original Weibo. As long as the sharing is valuable, people will be very enthusiastic to help forward it on Weibo. Also, the two differ in terms of user experience. On Twitter, people can only share text information, but on Sina people can also share photos, videos and audio. In addition, Sina Weibo also allows users to comment on Weibo content and forward it at the...

Claims

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Application Information

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IPC IPC(8): H04L29/08H04L12/26G06F17/30
Inventor 邹福泰姚雨石吴嘉玮
Owner SHANGHAI JIAO TONG UNIV
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