Method and system for identifying abnormal microblog users

A user and abnormal technology, applied in the field of social network security, can solve problems such as incompleteness and inaccurate detection results, and achieve the effect of high accuracy, low memory cost, and easy implementation.

Inactive Publication Date: 2013-06-12
INST OF INFORMATION ENG CAS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide an accurate, fast and efficient method and system for identifying abnorma

Method used

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  • Method and system for identifying abnormal microblog users
  • Method and system for identifying abnormal microblog users
  • Method and system for identifying abnormal microblog users

Examples

Experimental program
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Effect test

Example Embodiment

[0121] The second embodiment is a specific application of the first embodiment, and the data set used is the original data of the Sina Weibo platform, the largest domestic microblog platform, and all microblogs published by a total of 201,780 microblog users, including marketing and advertising accounts. After training the model for 98,100 authenticated users, the time to obtain the corresponding normal user behavior time feature vector is about 11 minutes. Using the vector to identify 201,780 users, the identification time is about 4 minutes. Among them, 5,089 machine users were detected, most of them were Advertising, marketing accounts. Therefore, in terms of training time, detection efficiency and detection quality, this method can meet the requirements of most of the current microblog platforms.

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Abstract

The invention relates to a method for identifying abnormal microblog users. The method comprises the steps of obtaining a plurality of users' microblog data, storing the microblog data into a database, taking statistical distribution of time intervals of user behaviors as behavior time characteristics of the users according to the microblog data of the users, generating behavior time characteristic vectors and defined parameters, calculating Kullback-Leibler divergence between the behavior time characteristic vectors of the normal users and the behavior time characteristic vectors of the users to be detected, judging the users to be detected with the calculated Kullback-Leibler divergence exceeding the defined parameters as the abnormal users, and extracting and showing keywords of contents of the abnormal users. The invention further provides a system for identifying the abnormal microblog users corresponding to the method. According to the method and system, the keywords of the blog article contents of the abnormal users can be extracted quickly, promulgators of junk information such as marketing and advertisements can be identified accurately, and the method and the system are applicable to detection of multiple microblog service platforms, and has the advantages of high accuracy and efficiency and wide applicability.

Description

technical field [0001] The invention relates to the field of social network security, in particular to a method and system for quickly identifying abnormal microblog users. Background technique [0002] At present, surfing the Internet has become an indispensable daily work for most people, and social networks such as Weibo are developing vigorously. The development of microblog has enriched the way and content of information dissemination, and brought about major changes in the formation and dissemination mechanism of network information. But at the same time, all kinds of spam are also spread wantonly on social networks. Abnormal users of Weibo use programs to spread spam on the Internet such as advertisements, topic hype, and product marketing. Therefore, how to effectively regulate the order of information dissemination in social networks is a great test we are facing today. [0003] Abnormal Weibo users refer to Weibo user accounts automatically generated by the progr...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F17/27
Inventor 王鹏张鹏刘铁男孙亮
Owner INST OF INFORMATION ENG CAS
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