{"title":"在假新闻检测中,时间很重要:简短回顾","authors":"Shubhangi Rastogi, D. Bansal","doi":"10.1109/CSCI54926.2021.00286","DOIUrl":null,"url":null,"abstract":"The prevalence of fake news has augmented with the rise of digital sources, especially social media. In this paper, current fake news research is studied and examined to offer a succinct road-map for future work. The paper presents a novel three-tier system depending on the lifespan of news and divides the research in three phases: early, mid and late-stage detection. The strategy to be followed for fake news detection varies with the time of detection. Fake news has shown adverse effects in a very short time period of propagation on social media. To mitigate this, it is required to detect fake news at an early stage when limited information about the news is available. In contrast, rich information can be examined like user engagement, propagation patterns, etc., at a later stage when news is deeply spread in the social network. Therefore, it is important to first analyze the time when the news disseminated, and then follow a suitable fake news detection methodology presented in the-state-of-the-art.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Time is Important in Fake News Detection: a short review\",\"authors\":\"Shubhangi Rastogi, D. Bansal\",\"doi\":\"10.1109/CSCI54926.2021.00286\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The prevalence of fake news has augmented with the rise of digital sources, especially social media. In this paper, current fake news research is studied and examined to offer a succinct road-map for future work. The paper presents a novel three-tier system depending on the lifespan of news and divides the research in three phases: early, mid and late-stage detection. The strategy to be followed for fake news detection varies with the time of detection. Fake news has shown adverse effects in a very short time period of propagation on social media. To mitigate this, it is required to detect fake news at an early stage when limited information about the news is available. In contrast, rich information can be examined like user engagement, propagation patterns, etc., at a later stage when news is deeply spread in the social network. Therefore, it is important to first analyze the time when the news disseminated, and then follow a suitable fake news detection methodology presented in the-state-of-the-art.\",\"PeriodicalId\":206881,\"journal\":{\"name\":\"2021 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCI54926.2021.00286\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI54926.2021.00286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time is Important in Fake News Detection: a short review
The prevalence of fake news has augmented with the rise of digital sources, especially social media. In this paper, current fake news research is studied and examined to offer a succinct road-map for future work. The paper presents a novel three-tier system depending on the lifespan of news and divides the research in three phases: early, mid and late-stage detection. The strategy to be followed for fake news detection varies with the time of detection. Fake news has shown adverse effects in a very short time period of propagation on social media. To mitigate this, it is required to detect fake news at an early stage when limited information about the news is available. In contrast, rich information can be examined like user engagement, propagation patterns, etc., at a later stage when news is deeply spread in the social network. Therefore, it is important to first analyze the time when the news disseminated, and then follow a suitable fake news detection methodology presented in the-state-of-the-art.