Social media post authenticity detection method based on hypergraph attention network

A technology of social media and detection methods, applied in the field of authenticity detection of social media posts based on hypergraph attention network, can solve problems such as data imbalance, insufficient modeling of post propagation structure, etc., to improve accuracy Effect

Active Publication Date: 2021-08-13
CENT SOUTH UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

Insufficient modeling of the propagation structure of posts
[0007] (2) There is a problem of data imbalance in the post data with labels

Method used

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  • Social media post authenticity detection method based on hypergraph attention network
  • Social media post authenticity detection method based on hypergraph attention network

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Embodiment Construction

[0075] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0076] Problem statement:

[0077] Posting data is published in similar forms on social media platforms such as Twitter, Reddit, and Weibo. Taking Twitter as an example, post data can be divided into sessions, branches, and tweet hierarchies. A posting session usually starts with a source tweet, leading to a certain topic or stating the occurrence of a certain event, and then other users comment on it to start a discussion, forming multiple chain replies.

[0078...

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Abstract

The invention relates to the technical field of poster detection, and discloses a social media poster authenticity detection method based on a hypergraph attention network, and the method specifically comprises the following steps: S1, carrying out the data preprocessing of social media poster text data, and dividing the data into a hierarchical structure of a session, a reply branch and a post; S2, carrying out post attribute feature extraction on the social media post text data processed in the step S1; S3, carrying out post text embedding on the social media post text data processed in the step S1; S4, splicing the vectors obtained in S2 and S3 to serve as graph nodes of the hypergraph structure; S5, taking the reply branches as hyperedges, forming a hypergraph by a set formed by the hyperedges and graph nodes, and inputting features of a hypergraph structure into a graph attention network for learning, so as to construct a hypergraph attention network model; and S6, using the hypergraph attention network model in the S5 to predict the authenticity of the source post. The hypergraph attention model is constructed, and the expression ability of the model is improved.

Description

technical field [0001] The invention relates to the technical field of post detection, in particular to a method for detecting the authenticity of social media posts based on a hypergraph attention network. Background technique [0002] With the rapid development of social media on the Internet, social media platforms such as Twitter, Weibo, and Facebook have become the main tools for information dissemination and information sharing. Social media breaks the barriers of physical distance between people. With its six characteristics of participation, openness, communication, dialogue, connectivity, and community, it increases the frequency of mutual communication, accelerates the speed of mutual communication, and expands the The breadth and depth of mutual communication. According to the 2020 Global Digital Report, 3.8 billion people around the world are using social media platforms, among which the daily active users of Twitter have reached 145 million, and the average dai...

Claims

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Application Information

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IPC IPC(8): G06F16/35G06F16/901G06F40/30G06Q50/00G06N20/00
CPCG06Q50/01G06F16/35G06F16/9024G06N20/00G06F40/30
Inventor 李芳芳宁肯张盼曦李伟
Owner CENT SOUTH UNIV
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