{"title":"Automatic detection of fake news on online platforms: A survey","authors":"Yasmine Lahlou, Sanaa El Fkihi, R. Faizi","doi":"10.1109/ICSSD47982.2019.9002823","DOIUrl":null,"url":null,"abstract":"In recent years, a lot of fake news are generated on the web in order to attract readership, influence opinions, and increase internet click revenue. The generation of this false information has become a worldwide phenomenon and its effects are notorious as it leads to confusion over facts and causes wrong decision-making.However, evaluating and detecting the veracity of news can be a complex and cumbersome task. This is simply because most of the studies carried out so far on the detection of such news, especially in real time, are not really performant.. Our objective in this work is, therefore, to review the major works that have addressed this problem. Results of this study have revealed that two major approaches have been put forward, namely linguistic and network. In this article, we will try to quote a set of automatic detection of false news on the web and social networks.","PeriodicalId":342806,"journal":{"name":"2019 1st International Conference on Smart Systems and Data Science (ICSSD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Smart Systems and Data Science (ICSSD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSD47982.2019.9002823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In recent years, a lot of fake news are generated on the web in order to attract readership, influence opinions, and increase internet click revenue. The generation of this false information has become a worldwide phenomenon and its effects are notorious as it leads to confusion over facts and causes wrong decision-making.However, evaluating and detecting the veracity of news can be a complex and cumbersome task. This is simply because most of the studies carried out so far on the detection of such news, especially in real time, are not really performant.. Our objective in this work is, therefore, to review the major works that have addressed this problem. Results of this study have revealed that two major approaches have been put forward, namely linguistic and network. In this article, we will try to quote a set of automatic detection of false news on the web and social networks.