COVID-19 Fake News Detector

被引：2

作者：

Liu, Junjie ^{[1
]}

Chen, Min ^{[1
]}

机构：

[1] Univ Washington Bothell, Comp & Software Syst, Bothell, WA 98011 USA

来源：

2023 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS, ICNC | 2023年

关键词：

COVID-19; deep learning; fake news detection; machine learning;

D O I：

10.1109/ICNC57223.2023.10074216

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

COVID-19 pandemic has been impacting people's everyday life for more than two years. With the fast spreading of online communication and social media platforms, the number of fake news related to COVID-19 is in a rapid growth and propagates misleading information to the public. To tackle this challenge and stop the spreading of fake news, this project proposes to build an online software detector specifically for COVID-19 news to classify whether the news is trustworthy. Specifically, as it is difficult to train a generic model for all domains, a base model is developed and fine-tuned to adapt the specific domain context. In addition, a data collection mechanism is developed to get latest COVID-19 news data and to keep the model fresh. We then conducted performance comparisons among different models using traditional machine learning techniques, ensemble machine learning, and the state-of-the-art deep learning mechanism. The most effective model is deployed to our online website for COVID-19 related fake news detection.

引用

页码：463 / 467

页数：5

共 27 条

[1] CoAID-DEEP: An Optimized Intelligent Framework for Automated Detecting COVID-19 Misleading Information on Twitter [J].

Abdelminaam, Diaa Salama ;

Ismail, Fatma Helmy ;

Taha, Mohamed ;

Taha, Ahmed ;

Houssein, Essam H. ;

Nabil, Ayman .

IEEE ACCESS, 2021, 9 :27840-27867

[2] Language-Independent Fake News Detection: English, Portuguese, and Spanish Mutual Features [J].

Abonizio, Hugo Queiroz ;

de Morais, Janaina Ignacio ;

Tavares, Gabriel Marques ;

Barbon Junior, Sylvio .

FUTURE INTERNET, 2020, 12 (05)

[3]

Ahmed S., 2022, arXiv

[4]

Cifuentes-Faura J., 2020, Comunicacin, V42, P100, DOI [10.18566/comunica.n42.a07, DOI 10.18566/COMUNICA.N42.A07]

[5]

Cui LM, 2020, Arxiv, DOI arXiv:2006.00885

[6]

Elhadad Mohamed K., 2021, Advances in Networked-Based Information Systems. 23rd International Conference on Network-Based Information Systems (NBiS-2020). Advances in Intelligent Systems and Computing (AISC 1264), P163, DOI 10.1007/978-3-030-57811-4_16

[7]

Felber T, 2021, Arxiv, DOI arXiv:2101.03717

[8] Behind the cues: A benchmarking study for fake news detection [J].

Gravanis, Georgios ;

Vakali, Athena ;

Diamantaras, Konstantinos ;

Karadais, Panagiotis .

EXPERT SYSTEMS WITH APPLICATIONS, 2019, 128 :201-213

[9]

Groza A, 2020, Arxiv, DOI arXiv:2004.12330

[10] Sentiment Analysis for Stock Price Prediction [J].

Gupta, Rubi ;

Chen, Min .

THIRD INTERNATIONAL CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR 2020), 2020, :213-218

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