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Rumor detection method based on linear and nonlinear propagation

A detection method, non-linear technology, applied in digital data information retrieval, instruments, biological neural network models, etc.

Active Publication Date: 2021-01-22
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0010] The purpose of the present invention is to overcome the technical defect that the existing rumor detection method only expresses and detects the propagation characteristics from a single aspect, and creatively proposes a rumor detection method based on linear and nonlinear propagation, which can detect the authenticity of rumors. accurate prediction

Method used

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  • Rumor detection method based on linear and nonlinear propagation
  • Rumor detection method based on linear and nonlinear propagation
  • Rumor detection method based on linear and nonlinear propagation

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Embodiment

[0051] The URLs of the two datasets selected in this embodiment are: https: / / www.zubiaga.org / datasets / .

[0052] Select a group of tweets in the "Ebola virus" event from the data set, and record the source node as v 1 ,[v 2 ,...,v n ] is the reply node, and analyze the authenticity label to which the source node belongs.

[0053] like figure 1 As shown, a rumor detection method based on linear and nonlinear propagation, including the following steps:

[0054] Step 1: Define the selected tweets as a graph: G=(V,E). V={v 1 ,...,v n} is the set of nodes, v 1 is the source (root) node, v i (2≤i≤n) represents the i-th reply (including comments and forwarding) node; E={e pc |p,c=1,2,...,n} is node v q to node v c The set of edges of . For any node v q , which all consist of a two-tuple v q ={s q ,t q} composition, s q represents text, t q Indicates the timestamp when the node text was published on the social media platform.

[0055] Step 2: For the text in each no...

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Abstract

The invention relates to a rumor detection method based on linear and nonlinear propagation, and belongs to the technical field of natural language understanding. According to the method, unified modeling representation is carried out on rumor nodes by utilizing text content and time information, and rumor detection is automatically carried out in a mode of combining linear and nonlinear propagation characteristics. Firstly, text information and time information contained in rumor nodes are used for carrying out joint representation on mixed features of the rumor nodes; then, node informationis aggregated along the linear time sequence and the nonlinear diffusion structure, expression of a source node is enhanced, and final propagation representation is formed. And finally, authenticity label prediction is carried out by using propagation representation. According to the method, node characteristics of rumors are extracted from two different angles, tree perception representation is obtained from a nonlinear diffusion mode, characteristics of propagation sequences are captured from linear time sequence interaction, and authenticity of the rumors can be accurately predicted.

Description

technical field [0001] The invention relates to a rumor detection method based on linear and nonlinear propagation, and belongs to the technical field of natural language understanding. Background technique [0002] With the rapid development of network technology, a large amount of false information has become ubiquitous on social media platforms, which has brought many adverse effects on society. Rumor detection aims to screen the information disseminated in social networks to detect which information is rumors. [0003] The spread of rumors is a complex and changeable phenomenon. In the process of rumor dissemination, in addition to the rumor itself, a large amount of social context information surrounding the rumor will be generated. Therefore, it is very important to understand the characteristics of rumors from both linear time series and nonlinear diffusion structure. The nonlinear diffusion structure reveals the path of rumor propagation in social networks, which ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9536G06F40/30G06N3/04
CPCG06F16/9536G06F40/30G06N3/044G06N3/045
Inventor 施重阳劳安
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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