{"title":"使用混合方法检测假新闻","authors":"Him Gohil, Vandana Joshi, Snehal Gandhi","doi":"10.17821/srels/2024/v61i2/171046","DOIUrl":null,"url":null,"abstract":"Over the last few years, fake news has dramatically increased on social media. Fake news can originate from any number of sources and is shared across different social platforms. This type of information is used to spread for fun or economic gain. Our goal is to stop distributing this type of misleading information on social media or any other platform. In this paper, we have proposed a hybrid model (RoBERTa and BERT) to detect fake news. Our proposed architecture is based on the LIAR multi-label dataset. Our model shows promising results.","PeriodicalId":513185,"journal":{"name":"Journal of Information and Knowledge","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fake News Detection Using Hybrid Approach\",\"authors\":\"Him Gohil, Vandana Joshi, Snehal Gandhi\",\"doi\":\"10.17821/srels/2024/v61i2/171046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the last few years, fake news has dramatically increased on social media. Fake news can originate from any number of sources and is shared across different social platforms. This type of information is used to spread for fun or economic gain. Our goal is to stop distributing this type of misleading information on social media or any other platform. In this paper, we have proposed a hybrid model (RoBERTa and BERT) to detect fake news. Our proposed architecture is based on the LIAR multi-label dataset. Our model shows promising results.\",\"PeriodicalId\":513185,\"journal\":{\"name\":\"Journal of Information and Knowledge\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information and Knowledge\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17821/srels/2024/v61i2/171046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Knowledge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17821/srels/2024/v61i2/171046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Over the last few years, fake news has dramatically increased on social media. Fake news can originate from any number of sources and is shared across different social platforms. This type of information is used to spread for fun or economic gain. Our goal is to stop distributing this type of misleading information on social media or any other platform. In this paper, we have proposed a hybrid model (RoBERTa and BERT) to detect fake news. Our proposed architecture is based on the LIAR multi-label dataset. Our model shows promising results.
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