Sakshi Kalra, Y. Bansal, Yashvardhan Sharma, G. S. Chauhan
{"title":"FakeSpotter: A blockchain-based trustworthy idea for fake news detection in social media","authors":"Sakshi Kalra, Y. Bansal, Yashvardhan Sharma, G. S. Chauhan","doi":"10.47974/jios-1411","DOIUrl":null,"url":null,"abstract":"Social media encourages information sharing without a physical barrier making it the perfect platform for learning and communication. In the meantime, it acts as a means of quickly disseminating misleading information. Researchers are battling fake news using strategies like detection, verification, mitigation, and analysis because of significant social concerns. It can be hard to tell the difference between true and false information. In the area of knowledge verification, various machine and deep learning-based approaches have been used to identify false data. However, there are some drawbacks of using AI-powered technologies, including data dependency, security concerns when applying AI-powered methods in the real world, and gaining user trust. In order to address the issues with AI-powered technologies, a blockchain-based idea (FakeSpotter) is put forth in this work. We offer an idea i.e.based on blockchain that utilizes crowdsourcing to determine whether or not content is fake. We attempt to use Blockchain technology’s features correctly and completely to create a secure system with no authoritative control over information dissemination. In this attempt, we aim to build a system that is not reliant on pre-defined datasets and discuss the initiatives taken in the fight against disinformation.","PeriodicalId":46518,"journal":{"name":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47974/jios-1411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Social media encourages information sharing without a physical barrier making it the perfect platform for learning and communication. In the meantime, it acts as a means of quickly disseminating misleading information. Researchers are battling fake news using strategies like detection, verification, mitigation, and analysis because of significant social concerns. It can be hard to tell the difference between true and false information. In the area of knowledge verification, various machine and deep learning-based approaches have been used to identify false data. However, there are some drawbacks of using AI-powered technologies, including data dependency, security concerns when applying AI-powered methods in the real world, and gaining user trust. In order to address the issues with AI-powered technologies, a blockchain-based idea (FakeSpotter) is put forth in this work. We offer an idea i.e.based on blockchain that utilizes crowdsourcing to determine whether or not content is fake. We attempt to use Blockchain technology’s features correctly and completely to create a secure system with no authoritative control over information dissemination. In this attempt, we aim to build a system that is not reliant on pre-defined datasets and discuss the initiatives taken in the fight against disinformation.