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Method for detecting sockpuppet

A detection method and network technology, applied in the direction of network data retrieval, network data indexing, and other database retrieval, etc., can solve problems such as inapplicability, and achieve the effect of increasing effectiveness

Active Publication Date: 2014-05-07
NANJING UNIV OF FINANCE & ECONOMICS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since multiple "network vests" of a person do not communicate frequently with each other, the traditional network model (undirected dense network) uses the number of interactions between users to measure the weight of network connection edges. does not apply, so we need to come up with a more accurate user interaction model

Method used

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  • Method for detecting sockpuppet

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Embodiment Construction

[0023] A detection method for "network vest", which includes three stages: firstly, construct a "similar viewpoint" network according to the interactive information of virtual social users; then tailor the "similar viewpoint" network according to the user's writing style; finally, use the community The discovery algorithm divides the trimmed "vest" network into communities, and IDs in the same community are regarded as a person's "network vest"; the implementation steps are as follows:

[0024] 1) Construct a network of "similar views" using given user interaction data in online communities;

[0025] 2) Select pairs of nodes from the "similar viewpoint" network , Extract all the comments published by these two IDs from the corpus database, and construct two sample sets; call the T test to determine whether there is a significant difference between the two comment sample sets; if there is no significant difference between the two samples, the node pair The boundary is preserv...

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Abstract

The invention discloses a method for detecting a 'sockpuppet' based on a 'similar view' network and an article author judging technique. The method comprises the three steps that first, the 'similar view' network is established according to the mutual information of virtual social users; then the 'similar view' network is cut according to the writing styles of the users; at last, a community discovery algorithm is used for conducting community dividing on the cut 'sockpuppet' network, and the IDs in the same community are considered as the 'sockpuppet' of a certain person. The method for detecting the 'sockpuppet' has the following advantages of following the actual significance of the 'sockpuppet' community, being capable of being applied to detecting the 'sockpuppet' under a real-time network environment, and increasing the effectiveness of community discovery. The method for detecting the 'sockpuppet' is mainly applied to the various fields of public opinion analysis in virtual space, 'sockpuppet' detection and the like.

Description

technical field [0001] The invention belongs to the field of Web mining, and relates to a virtual space "network vest" intelligent detection technology, specifically a "network vest" detection method based on "similar point of view" network and article author identification technology. Background technique [0002] In online communities, some users communicate with other users by using multiple usernames or by disguising themselves as other users (often referred to as "network vests"). Some members of online communities, in order to confuse the public, use some artificial "network vests" to pretend to be different users, and praise or deny a certain product or a certain person's work. What's more, create a certain Internet rumor, and then use different Internet "vests" to spread it. [0003] For a long time, there have been very few relevant literatures on the detection technology of "network vests", and some related work can be applied to the detection of "network vests". ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/951
Inventor 卜湛伍之昂曹杰李秀怡方昌健刘英卓
Owner NANJING UNIV OF FINANCE & ECONOMICS
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