Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A social robot recognition method based on graph attention network

A technology of attention and robotics, which is applied in the fields of instruments, computing, and electronic digital data processing, etc., can solve problems such as bad content, and achieve the effect of reducing opportunities to take advantage of, weakening the influence of bad public opinion, and maintaining social harmony and stability

Active Publication Date: 2021-04-06
HANGZHOU DIANZI UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In recent years, with the development of social networks, individuals can fully express their voices on the Internet, but it also gives criminals an opportunity to publish bad content on the Internet.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A social robot recognition method based on graph attention network
  • A social robot recognition method based on graph attention network
  • A social robot recognition method based on graph attention network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] Such as figure 1 As shown, the social robot identification method of the present invention, the steps are as follows:

[0034] Step (1), collect a certain piece of content posted by some users on Weibo within one day and the mutual comment relationship, and the number of accounts is about 3000. Record the content posted by an account on the social platform, and collect the substantive comment content and comments posted by the comment account under the content at the same time. At the same time, judge whether the account is a robot based on the content posted by the account and the comment relationship.

[0035] figure 2 It is a schematic diagram of the social network in the present invention.

[0036] Step (2), performing natural language processing on the substantive content published by all collected accounts to obtain a data set. Firstly, high-frequency words such as "de" and "yes" are removed. Then select about 1500 commonly used words and arrange them in a c...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a social robot recognition method based on a graph attention network. The method of the present invention is based on the graph attention network, by performing natural language processing on the content published on the social network to construct node features, forwarding and commenting relationships between social accounts to construct a graph, and then classifying, thereby judging whether the account is a social robot. First, social network data is created to create a data set, and then the graph attention network is constructed, and the graph attention network is trained and tested through the created data set. Aiming at the problem of complex social network robot identification, the method of the present invention can automatically and efficiently identify social robots, reduce opportunities for criminals to take advantage of, thereby limiting speech released by robots, weakening the influence of bad public opinion, and helping to maintain social harmony and stability.

Description

technical field [0001] The present invention relates to the application field of the graph attention network, in particular to the node classification technology based on the graph attention network and its actual application to the field of social networks. Background technique [0002] In recent years, with the development of social networks, individuals can fully express their voices on the Internet, but it also gives criminals an opportunity to publish bad content on the Internet. Especially on Weibo, which is full of trolls and zombie fans, social robots can publish a large amount of content to influence the direction of public opinion. Therefore, a system is needed to identify social robots and control the social impact of the speeches released by robots. [0003] In computer science, a graph is a data structure consisting of vertices and edges. A graph G can be described by a set of vertices V and the edges E it contains, namely: [0004] G=(V,E) (1) [0005] Verti...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9536
CPCG06F16/9536
Inventor 颜成钢阮定孙垚棋张继勇张勇东
Owner HANGZHOU DIANZI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com