Microblog social robot detection method based on deep neural network

Abstract

The invention discloses a microblog social robot detection method based on a deep neural network. The method comprises the steps of constructing an artificial mark data set, extracting classificationfeatures of user data, and constructing a deep neural network model based on a residual neural network, a bidirectional gating circulation unit and an attention mechanism to perform Sina microblog social robot detection. User data of Sina microblogs are obtained through web crawlers, behaviors of users and robots are analyzed, classification features of the user data are extracted from four different perspectives, and the social robots can be detected more comprehensively and accurately by means of the features; and the deep neural network model is constructed by combining the residual neuralnetwork, the bidirectional gating circulation unit and the attention mechanism, so that the accuracy and the stability of the detection model can be remarkably improved.

Description

Technical field [0001] The invention belongs to the technical field of social robot detection, and specifically relates to a microblog social robot detection method based on a deep neural network. Background technique [0002] In recent years, with the rapid development of information technology, online social networks (OSNs) have appeared in people's daily lives. As OSNs are widely used by people, a social robot account of abnormal users has appeared. At first, these social robots were used to serve humans to improve people's quality of life. However, these social robots have begun to be used for some undesirable and even illegal purposes, so that they have had a great negative impact on the entire OSNs and people's daily lives. . [0003] In the existing OSNs, social robots are a type of special purpose accounts controlled by programs. They are often used for illegal sabotage or profit, including publishing large amounts of advertising information, spreading malicious URL links...

AI Technical Summary

Problems solved by technology

Many research works only focus on extracting the characteristics of a certain aspect of social robots, but cannot achieve a comprehensive description of social robots.

At the same time, even if there are works that extract the features of social robots from multiple perspectives, there are still problems with a small number of features, and it is difficult to fully describe the problem of social robots

[0007] The second problem is that traditional detection models are difficult to effectively solve the problem of social robot detection in the current social network environment

Most of the previous studies have used relatively simple machine learning models to detect social robots in Sina Weibo. Although some results have been achieved, there is still a lot of room for improvement.

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