The PLOS One Editors issued an Editorial Note regarding the article titled “Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society” by Zamir et al. The note informs readers that specific cited sources within that article appear not to support the statements for which they were cited. The Editorial Note itself is concise and designed to alert readers about interpretation of the original paper.
The Editorial Note identifies the affected research article with full bibliographic detail: 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 includes links to the article, its PDF, and external indexing entries such as PubMed/NCBI and Google Scholar.
The Editorial Note states that References 13, 17, and 71 cited in the Zamir et al. article “do not appear to support the corresponding cited statements.” The note does not provide further breakdown of which statements are unsupported, how they were used in the article, or the exact nature of the mismatch between citation and claim.
The note was published by The PLOS One Editors on September 3, 2026, and is assigned DOI 10.1371/journal.pone.0357518. It is published as an open access Editorial Note and distributed under the Creative Commons Attribution License. The notice appears in PLOS One’s record for the article and is linked via the journal’s CrossMark and article metrics systems.
The Editorial Note communicates a specific concern (that three references do not appear to support cited statements) but does not include additional details such as: which passages in the Zamir et al. article are affected, the specific content of References 13, 17, and 71, or any author responses or corrections. The Editorial Note therefore functions as an alert; further specifics were not reported in the note.
The Editorial Note includes direct links to the affected article’s page, the downloadable PDF, and external bibliographic entries (PubMed/NCBI, Google Scholar). It also references the related PLOS article page and CrossMark status to indicate provenance and to allow readers to follow updates. Readers seeking context are directed to consult the cited article and its reference list directly.
This Editorial Note is intended to inform readers that some citations in the Zamir et al. article may not substantiate the statements for which they were referenced. Because the note does not present detailed examples or an author-led correction, readers should interpret the affected article with caution and consult the original references and the Zamir et al. text when evaluating specific claims. The Editorial Note does not announce a retraction or formal correction within its content; it serves as a publisher-issued notice to aid interpretation.
Readers who require more information are directed to the Zamir et al. article page (which includes the full reference list), the linked indexing entries, and the comments and metrics sections maintained on the article’s PLOS One record. The Editorial Note itself does not list subsequent actions or responses; any further editorial steps, author statements, or corrections would be published separately if taken by the journal.
In summary, the PLOS One Editors published a brief Editorial Note on September 3, 2026, flagging that References 13, 17, and 71 in the 2024 Zamir et al. article do not appear to support the corresponding cited statements. The note provides identification and links but does not detail the mismatches or include corrective text; those specifics were not reported in the Editorial Note.