{"title":"开发智能手机应用程序和 Chrome 浏览器扩展程序,以检测英语和葡萄牙语假新闻","authors":"Ricardo Afonso;João Rosas","doi":"10.1109/TLA.2024.10472958","DOIUrl":null,"url":null,"abstract":"In a digital society, the truth portrayed by information is crucial in promoting education, security, and evolution. However, fake news raises a significant concern in that regard. Although there has been a continuous effort in the fight against fake news, it is still a multifaceted challenge in constant change as the menace renovates itself. Thus, in our approach, several machine learning and deep learning models were developed to obtain models that can detect fake content that appears online. The models can then be interfaced with users devices, namely in the form of browser extensions and smartphone applications. The classification models run on a cloud server and are accessible via web services. These models can detect fake news in English and European Portuguese, with a stronger focus on the latter, given the reduced number of projects in this specific field and language. Besides developing the first public dataset for fake news detection in European Portuguese through web scraping, the models achieved better performance than previous work while being trained with a significantly higher amount of data from a wider variety of sources.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10472958","citationCount":"0","resultStr":"{\"title\":\"Development of a Smartphone Application and Chrome Extension to Detect Fake News in English and European Portuguese\",\"authors\":\"Ricardo Afonso;João Rosas\",\"doi\":\"10.1109/TLA.2024.10472958\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a digital society, the truth portrayed by information is crucial in promoting education, security, and evolution. However, fake news raises a significant concern in that regard. Although there has been a continuous effort in the fight against fake news, it is still a multifaceted challenge in constant change as the menace renovates itself. Thus, in our approach, several machine learning and deep learning models were developed to obtain models that can detect fake content that appears online. The models can then be interfaced with users devices, namely in the form of browser extensions and smartphone applications. The classification models run on a cloud server and are accessible via web services. These models can detect fake news in English and European Portuguese, with a stronger focus on the latter, given the reduced number of projects in this specific field and language. Besides developing the first public dataset for fake news detection in European Portuguese through web scraping, the models achieved better performance than previous work while being trained with a significantly higher amount of data from a wider variety of sources.\",\"PeriodicalId\":55024,\"journal\":{\"name\":\"IEEE Latin America Transactions\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10472958\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Latin America Transactions\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10472958/\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Latin America Transactions","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10472958/","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Development of a Smartphone Application and Chrome Extension to Detect Fake News in English and European Portuguese
In a digital society, the truth portrayed by information is crucial in promoting education, security, and evolution. However, fake news raises a significant concern in that regard. Although there has been a continuous effort in the fight against fake news, it is still a multifaceted challenge in constant change as the menace renovates itself. Thus, in our approach, several machine learning and deep learning models were developed to obtain models that can detect fake content that appears online. The models can then be interfaced with users devices, namely in the form of browser extensions and smartphone applications. The classification models run on a cloud server and are accessible via web services. These models can detect fake news in English and European Portuguese, with a stronger focus on the latter, given the reduced number of projects in this specific field and language. Besides developing the first public dataset for fake news detection in European Portuguese through web scraping, the models achieved better performance than previous work while being trained with a significantly higher amount of data from a wider variety of sources.
期刊介绍:
IEEE Latin America Transactions (IEEE LATAM) is an interdisciplinary journal focused on the dissemination of original and quality research papers / review articles in Spanish and Portuguese of emerging topics in three main areas: Computing, Electric Energy and Electronics. Some of the sub-areas of the journal are, but not limited to: Automatic control, communications, instrumentation, artificial intelligence, power and industrial electronics, fault diagnosis and detection, transportation electrification, internet of things, electrical machines, circuits and systems, biomedicine and biomedical / haptic applications, secure communications, robotics, sensors and actuators, computer networks, smart grids, among others.