Annealing attention rumor identification method and device based on user features

A technology of user characteristics and attention, applied in the field of social network security, can solve the problems of high labor demand and poor effect of early rumor identification, and achieve the effect of high computational efficiency, versatility and high accuracy

Active Publication Date: 2021-08-03
WUHAN UNIV
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Problems solved by technology

[0006] The present invention mainly solves the problems that the above-mentioned traditional machine learning model has high labor requirements, the end-to-end method focuses on the text content features, the use of user features is too simple, and the early rumor identification effect is not good, and it provides an annealing method based on user features Attention rumor identification method and device

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  • Annealing attention rumor identification method and device based on user features
  • Annealing attention rumor identification method and device based on user features
  • Annealing attention rumor identification method and device based on user features

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Embodiment

[0075] The present invention mainly solves the above-mentioned problems that the traditional machine learning model has high labor requirements, the end-to-end method focuses on the text content features, the use of user features is too simple, and the early rumor identification effect is not good. In order to facilitate the detection of our inventive device process, now with figure 1 The model framework in , as an example to illustrate the process of rumor detection.

[0076] From figure 1 As can be seen in , the input user feature matrix data is learned and extracted through the annealed attention layer and the multi-layer perceptron. After extracting the time series attention weight matrix and the inter-feature attention weight matrix, they are combined with the original feature matrix information. Then throw another multi-layer perceptron to extract high-level representation vectors. Finally, the high-level representation vector is used as the input of the fully connect...

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Abstract

The invention relates to a detection method for rumors in an online social network, belongs to the technical field of social network security, and particularly relates to an annealing attention rumor identification method and device based on user features. According to the method and device, a public social network platform rumor identification data set is adopted, social network user features in a rumor propagation period are utilized, and a parameterized annealing function-based method is provided for time sequence attention learning of the social network user features. A multi-layer perceptron is used for carrying out attention learning and advanced representation extraction among features, a full-connection neural network is used for carrying out rumor identification and classification, and the feasibility of the method on a real world data set is verified.

Description

technical field [0001] The invention relates to a method for detecting rumors in an online social network, belonging to the technical field of social network security, and in particular to an annealing attention rumor identification model based on user characteristics. Background technique [0002] With the popularity of the Internet and various social applications, online social networks have become an indispensable information source platform in daily life. Organizations and individuals can freely publish information, communicate and discuss with others in such online social networks. Online social networks have brought convenience for people to share information and favorable conditions for the spread of rumors. Malicious individuals or organizations spread rumors for different purposes, causing various adverse consequences, such as political manipulation, economic losses, social panic, etc. Therefore, it is crucial to detect rumors as early as possible to prevent them ...

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Application Information

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IPC IPC(8): G06F16/35G06F16/38G06K9/62G06N3/00G06N3/04G06N3/08
CPCG06F16/35G06F16/38G06N3/006G06N3/08G06N3/047G06F18/2415
Inventor 王丽娜骆正武王文琦叶傲霜柯剑鹏
Owner WUHAN UNIV
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