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ProBlock:一种检测虚假新闻的新方法。

ProBlock: a novel approach for fake news detection.

作者信息

Sengupta Eishvak, Nagpal Renuka, Mehrotra Deepti, Srivastava Gautam

机构信息

Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, India.

Department of Mathematics and Computer Science, Brandon University, Brandon, R7A 6A9 Canada.

出版信息

Cluster Comput. 2021;24(4):3779-3795. doi: 10.1007/s10586-021-03361-w. Epub 2021 Aug 4.

Abstract

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.

摘要

世界正日益深入数字时代,第一手信息来源正转向社交媒体和在线新闻门户网站。由于我们对信息来源的依赖变得模糊不清,被误导的可能性成倍增加。传统新闻来源遵循严格的操作规范来核实报道,而如今,用户可以在社交媒体和未经核实的门户网站上上传新闻条目,却无需证明其真实性。互联网上缺乏此类新闻文章真实性的任何判定因素,这就需要一种新颖的方法,通过利用技术来确定未经核实新闻条目的真实性系数。本研究提出了一个带有安全投票系统的动态模型,新闻审核人员可以在其中对新闻提供反馈,并且使用概率数学模型根据收到的反馈来预测新闻条目的真实性。还提出了一种基于区块链的模型ProBlock,以确保所传播信息的正确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c17/8335474/819e7729a1ce/10586_2021_3361_Fig1_HTML.jpg

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