---
title: "PLOS ONE Editorial Note: Cited References in COVID-19 Sentiment Analysis Article Do Not Support St"
id: "plos-one-16-editorial-note-machine-and-deep-learning-algorithms-for-sentiment-analysis"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-16-editorial-note-machine-and-deep-learning-algorithms-for-sentiment-analysis"
content_type: "clinical_feed_article"
specialty: "General"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357518"
published_at: "2026-09-03T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# PLOS ONE Editorial Note: Cited References in COVID-19 Sentiment Analysis Article Do Not Support St
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-16-editorial-note-machine-and-deep-learning-algorithms-for-sentiment-analysis
- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357518)
- **Published At:** 2026-09-03T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The PLOS One Editors published an **Editorial Note** concerning the article “Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society” by Zamir et al. (2024). - The note states that References **13, 17, and 71** cited in that article “do not appear to support the corresponding cited statements.” - The Editorial Note identifies the affected article by full citation: Zamir MT, Ullah F, Tariq R, Bangyal WH, Arif M, Gelbukh A. Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society. PLoS One. 2024;19(12):e0315407; pmid:39700256. - The Editorial Note was published by The PLOS One Editors on September 3, 2026, and is cataloged with DOI 10.1371/journal.pone.0357518. - The notice does not elaborate on the precise nature of the mismatches between the cited references and the statements they were used to support; details were not reported in the Editorial Note. - The Editorial Note is open access under the Creative Commons Attribution License and links to the original article and its PubMed/NCBI and Google Scholar entries. - The Editorial Note is presented as an update to inform readers about interpretation of the Zamir et al. article; no retraction, correction text, or author response is included in the note itself. - The Editorial Note includes links to the affected article and related materials (PDF, metrics, comments) and is connected to PLOS’s CrossMark update system; readers are directed to the referenced article for context.
## Clinical Analysis & Structured Key Points
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[See all article types » ](https://journals.plos.org/plosone/s/other-article-types) # Editorial Note: Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society * The PLOS One Editors # Editorial Note: Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society * The PLOS One Editors ![PLOS](https://journals.plos.org/resource/img/logo-plos-full-color.svg) x * Published: September 3, 2026 * * [Article](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357518) * [Metrics](https://journals.plos.org/plosone/article/metrics?id=10.1371/journal.pone.0357518) * [Comments](https://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0357518) * [Media Coverage](http://plos.altmetric.com/details/doi/10.1371/journal.pone.0357518) * [Reference](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357518#reference) * [Reader Comments](https://journals.plos.org/plosone/article/comments?id=10.1371/journal.pone.0357518) The _PLOS One_ Editors issue this Editorial Note to inform readers that the articles cited in this article [[1](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0357518#pone.0357518.ref001)] as References 13, 17, and 71 do not appear to support the corresponding cited statements. ## Reference 1. 1. Zamir MT, Ullah F, Tariq R, Bangyal WH, Arif M, Gelbukh A. Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society. PLoS One. 2024;19(12):e0315407. pmid:39700256 * [ View Article ](https://doi.org/10.1371/journal.pone.0315407 "Go to article") * [ PubMed/NCBI ](http://www.ncbi.nlm.nih.gov/pubmed/39700256 "Go to article in PubMed") * [ Google Scholar ](http://scholar.google.com/scholar?q=Machine+and+deep+learning+algorithms+for+sentiment+analysis+during+COVID-19%3A+A+vision+to+create+fake+news+resistant+society+Zamir+2024 "Go to article in Google Scholar") **Citation:** The _PLOS One_ Editors (2026) Editorial Note: Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society. PLoS One 21(9): e0357518. https://doi.org/10.1371/journal.pone.0357518 **Published:** September 3, 2026 **Copyright:** © 2026 The PLOS One Editors. This is an open access article distributed under the terms of the [Creative Commons Attribution License](http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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) 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