Cargando…
ProBlock: a novel approach for fake news detection
The world is diving deeper into the digital age, and the sources of first information are moving towards social media and online news portals. The chances of being misinformed increase multifold as our reliance on sources of information are getting ambiguous. Traditional news sources followed strict...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8335474/ https://www.ncbi.nlm.nih.gov/pubmed/34366702 http://dx.doi.org/10.1007/s10586-021-03361-w |
_version_ | 1783733113811107840 |
---|---|
author | Sengupta, Eishvak Nagpal, Renuka Mehrotra, Deepti Srivastava, Gautam |
author_facet | Sengupta, Eishvak Nagpal, Renuka Mehrotra, Deepti Srivastava, Gautam |
author_sort | Sengupta, Eishvak |
collection | PubMed |
description | The world is diving deeper into the digital age, and the sources of first information are moving towards social media and online news portals. The chances of being misinformed increase multifold as our reliance on sources of information are getting ambiguous. Traditional news sources followed strict codes of practice to verify stories, whereas today, users can upload news items on social media and unverified portals without proving their veracity. The absence of any determinants of such news articles’ truthfulness on the Internet calls for a novel approach to determine the realness quotient of unverified news items by leveraging technology. This study presents a dynamic model with a secure voting system, where news reviewers can provide feedback on news, and a probabilistic mathematical model is used for predicting the truthfulness of the news item based on the feedback received. A blockchain-based model, ProBlock is proposed; so that correctness of information propagated is ensured. |
format | Online Article Text |
id | pubmed-8335474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-83354742021-08-04 ProBlock: a novel approach for fake news detection Sengupta, Eishvak Nagpal, Renuka Mehrotra, Deepti Srivastava, Gautam Cluster Comput Article The world is diving deeper into the digital age, and the sources of first information are moving towards social media and online news portals. The chances of being misinformed increase multifold as our reliance on sources of information are getting ambiguous. Traditional news sources followed strict codes of practice to verify stories, whereas today, users can upload news items on social media and unverified portals without proving their veracity. The absence of any determinants of such news articles’ truthfulness on the Internet calls for a novel approach to determine the realness quotient of unverified news items by leveraging technology. This study presents a dynamic model with a secure voting system, where news reviewers can provide feedback on news, and a probabilistic mathematical model is used for predicting the truthfulness of the news item based on the feedback received. A blockchain-based model, ProBlock is proposed; so that correctness of information propagated is ensured. Springer US 2021-08-04 2021 /pmc/articles/PMC8335474/ /pubmed/34366702 http://dx.doi.org/10.1007/s10586-021-03361-w Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Sengupta, Eishvak Nagpal, Renuka Mehrotra, Deepti Srivastava, Gautam ProBlock: a novel approach for fake news detection |
title | ProBlock: a novel approach for fake news detection |
title_full | ProBlock: a novel approach for fake news detection |
title_fullStr | ProBlock: a novel approach for fake news detection |
title_full_unstemmed | ProBlock: a novel approach for fake news detection |
title_short | ProBlock: a novel approach for fake news detection |
title_sort | problock: a novel approach for fake news detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8335474/ https://www.ncbi.nlm.nih.gov/pubmed/34366702 http://dx.doi.org/10.1007/s10586-021-03361-w |
work_keys_str_mv | AT senguptaeishvak problockanovelapproachforfakenewsdetection AT nagpalrenuka problockanovelapproachforfakenewsdetection AT mehrotradeepti problockanovelapproachforfakenewsdetection AT srivastavagautam problockanovelapproachforfakenewsdetection |