Network rumor detection method based on pre-trained language model

A technology of language model and detection method, applied in neural learning methods, biological neural network models, natural language data processing, etc., can solve problems such as unavailable structural features, difficult to obtain semantic information, complex writing formats, etc., and achieve good generalization performance, preprocessing simple effects

Active Publication Date: 2020-05-12
BEIJING RES INST UNIV OF SCI & TECH OF CHINA +1
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  • Application Information

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Problems solved by technology

[0005] However, these methods have significant disadvantages
First, the text information on social media is short and concise, the grammar is irregular, the writing format is complicated...

Method used

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  • Network rumor detection method based on pre-trained language model
  • Network rumor detection method based on pre-trained language model
  • Network rumor detection method based on pre-trained language model

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Embodiment Construction

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0018] An embodiment of the present invention provides a method for detecting network rumors based on a pre-trained language model, such as figure 1 As shown, it mainly includes:

[0019] 1. Obtain the source text to be detected and the forwarded text of multiple other users.

[0020] In the embodiment of the present invention, the text in the microblog platform is taken as an example for introduction. That is, the source text may be a source mic...

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Abstract

The invention discloses a network rumor detection method based on a pre-trained language model. The network rumor detection method comprises the steps of obtaining a to-be-detected source text and forwarded texts of a plurality of other users; preprocessing the source text and forwarding texts of a plurality of other users respectively, and connecting the preprocessed forwarding texts to obtain aset of the forwarding texts; regarding a set of the preprocessed source text and the forwarded text as a pair of sentences; and constructing a linear sequence, inputting the linear sequence into the pre-trained language model, mining a semantic relationship between the source text and the forwarded text through the pre-trained language model, and obtaining the probability that the source text is arumor or a non-rumor through a full connection layer and a softmax function. According to the method, helpful high-level semantic features can be automatically learned and acquired without dependingon specific prior knowledge, so that the method has good generalization. The method does not need to depend on a large amount of forwarding/commenting information related to the source text, and earlydetection can be achieved.

Description

technical field [0001] The invention relates to the technical field of rumor detection, in particular to a method for detecting network rumors based on a pre-trained language model. Background technique [0002] With the development of Internet technology and the rise of smart terminal devices, social media platforms provide convenient channels for people to share a variety of news, and people can quickly upload massive multimedia data through simple operations. However, Internet rumors can also be used to spread widely and mislead the public. Bad rumors can guide public opinion, cause panic among the people, and affect the credibility of the government. Therefore, to ensure that users can get reliable news and maintain social order, detecting rumors on social media is an important task. [0003] Traditional online rumor detection methods rely on feature engineering, such as manually extracting features from user published messages and user personal information, and then a...

Claims

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Application Information

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IPC IPC(8): G06F40/30G06F40/289G06F16/215G06F16/9536G06Q50/00G06K9/62G06N3/04G06N3/08
CPCG06F16/215G06F16/9536G06Q50/01G06N3/084G06N3/045G06F18/24323
Inventor 张勇东毛震东邓旭冉付哲仁
Owner BEIJING RES INST UNIV OF SCI & TECH OF CHINA
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