A Novel Rumor Detection Method Based on Non-Consecutive Semantic Features and Comment Stance-Reference-Cited by-同舟云学术

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A Novel Rumor Detection Method Based on Non-Consecutive Semantic Features and Comment Stance

Published:2023 Issue: Volume:11 Page:58016-58024
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhu Yi¹,Wang Gensheng²^ORCID,Li Sheng³,Huang Xuejian³^ORCID

Affiliation:

1. School of Finance, Taxation and Public Administration, Jiangxi University of Finance and Economics, Nanchang, China

2. School of International Economics and Trade, Jiangxi University of Finance and Economics, Nanjing, China

3. School of Humanities, Jiangxi University of Finance and Economics, Nanchang, China

Funder

National Natural Science Foundation of China

Science and Technology Project of Jiangxi Provincial Department of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10146266.pdf?arnumber=10146266

Reference39 articles.

1. A lightweight propagation path aggregating network with neural topic model for rumor detection

2. KAGN:knowledge-powered attention and graph convolutional networks for social media rumor detection

3. DSS: A hybrid deep model for fake news detection using propagation tree and stance network

4. Rumor detection on social media using hierarchically aggregated feature via graph neural networks

5. Detecting rumors from microblogs with recurrent neural networks;ma;Proc AAAI,2016

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transformer-based models for combating rumours on microblogging platforms: a review;Artificial Intelligence Review;2024-07-20

2. Hybrid approach of deep feature extraction using BERT– OPCNN & FIAC with customized Bi-LSTM for rumor text classification;Alexandria Engineering Journal;2024-03

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