ArticleComputational and mathematical methods in medicine2021
Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Automated detection of corruption reports in text via deep reinforcement learning.Scientific reports · 2025Article
- Explainable AI-Driven Analysis of Radiology Reports Using Text and Image Data: Experimental Study.JMIR formative research · 2025Article
- Machine learning driven dashboard for chronic myeloid leukemia prediction using protein sequences.PloS one · 2025Article
- Navigating tenses in Bengali sentences: A stacked ensemble model for enhanced prediction.PloS one · 2025Article
- Article
- Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society.PloS one · 2024Article
- Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society.PloS one · 2024Article
- Comprehensively identifying Long Covid articles with human-in-the-loop machine learning.Patterns (New York, N.Y.) · 2023Article
- Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study.JMIR medical informatics · 2022Article
- A Divide-and-Conquer Bat Algorithm with Direction of Mean Best Position for Optimization of Cutting Parameters in CNC Turnings.Computational intelligence and neuroscience · 2022Article
- VGG-UNet/VGG-SegNet Supported Automatic Segmentation of Endoplasmic Reticulum Network in Fluorescence Microscopy Images.Scanning · 2022Article
- Health Misinformation Detection: Approaches, Challenges and Opportunities.Inquiry : a journal of medical care organization, provision and financingReview
- Utilizing deep learning models for ternary classification in COVID-19 infodemic detection.Digital healthArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A vast amount of data is generated every second for microblogs, content sharing via social media sites, and social networking. Twitter is an essential popular microblog where people voice their opinions about daily issues. Recently, analyzing these opinions is the primary concern of Sentiment analysis or opinion mining. Efficiently capturing, gathering, and analyzing sentiments have been challenging for researchers. To deal with these challenges, in this research work, we propose a highly accurate approach for SA of fake news on COVID-19. The fake news dataset contains fake news on COVID-19; we started by data preprocessing (replace the missing value, noise removal, tokenization, and stemming). We applied a semantic model with term frequency and inverse document frequency weighting for data representation. In the measuring and evaluation step, we applied eight machine-learning algorithms such as Naive Bayesian, Adaboost,
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.