打击社交媒体假新闻的趋势——一项调查

IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Information and Telecommunication Pub Date : 2020-11-27 DOI:10.1080/24751839.2020.1847379
Botambu Collins, Dinh Tuyen Hoang, N. Nguyen, D. Hwang
{"title":"打击社交媒体假新闻的趋势——一项调查","authors":"Botambu Collins, Dinh Tuyen Hoang, N. Nguyen, D. Hwang","doi":"10.1080/24751839.2020.1847379","DOIUrl":null,"url":null,"abstract":"ABSTRACT Social media following its introduction has witnessed a lot of scholarly attention in recent years due to its growing popularity. These various social media sites have become the mecca of information because of their less costly and easy accessibility. Although these sites were developed to enhance our lives, they are seen as both angelic and vicious. Growing misinformation and fake content by malicious users have not only plagued our online social media ecosystem into chaos, but it also meted untold suffering to humankind. Recently, social media has witnessed a reverberation amid the proliferation of fake news which has made people reluctant to engage in genuine news sharing for fear that such information is false. Consequently, there is a dire need for these fake content to be detected and removed from social media. This study explores the various methods of combating fake news on social media such as Natural Language Processing, Hybrid model. We surmised that detecting fake news is a challenging and complex issue, however, it remains a workable task. Revelation in this study holds that the application of hybrid-machine learning techniques and the collective effort of humans could stand a higher chance of fighting misinformation on social media.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24751839.2020.1847379","citationCount":"50","resultStr":"{\"title\":\"Trends in combating fake news on social media – a survey\",\"authors\":\"Botambu Collins, Dinh Tuyen Hoang, N. Nguyen, D. Hwang\",\"doi\":\"10.1080/24751839.2020.1847379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Social media following its introduction has witnessed a lot of scholarly attention in recent years due to its growing popularity. These various social media sites have become the mecca of information because of their less costly and easy accessibility. Although these sites were developed to enhance our lives, they are seen as both angelic and vicious. Growing misinformation and fake content by malicious users have not only plagued our online social media ecosystem into chaos, but it also meted untold suffering to humankind. Recently, social media has witnessed a reverberation amid the proliferation of fake news which has made people reluctant to engage in genuine news sharing for fear that such information is false. Consequently, there is a dire need for these fake content to be detected and removed from social media. This study explores the various methods of combating fake news on social media such as Natural Language Processing, Hybrid model. We surmised that detecting fake news is a challenging and complex issue, however, it remains a workable task. Revelation in this study holds that the application of hybrid-machine learning techniques and the collective effort of humans could stand a higher chance of fighting misinformation on social media.\",\"PeriodicalId\":32180,\"journal\":{\"name\":\"Journal of Information and Telecommunication\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2020-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/24751839.2020.1847379\",\"citationCount\":\"50\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information and Telecommunication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/24751839.2020.1847379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Telecommunication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24751839.2020.1847379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 50

摘要

近年来,由于社交媒体的日益普及,它的出现引起了学术界的广泛关注。这些各种各样的社交媒体网站已经成为信息的圣地,因为它们成本较低,易于访问。虽然这些网站是为了改善我们的生活而开发的,但它们被视为既天使又邪恶。恶意用户越来越多的错误信息和虚假内容,不仅使我们的网络社交媒体生态系统陷入混乱,而且给人类带来了难以言表的痛苦。最近,社交媒体见证了假新闻泛滥的反响,这使得人们不愿参与真正的新闻分享,因为担心这些信息是虚假的。因此,迫切需要从社交媒体上发现和删除这些虚假内容。本研究探讨了在社交媒体上打击假新闻的各种方法,如自然语言处理,混合模型。我们推测,检测假新闻是一个具有挑战性和复杂的问题,然而,它仍然是一个可行的任务。这项研究的启示认为,混合机器学习技术的应用和人类的集体努力可以更有可能打击社交媒体上的错误信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Trends in combating fake news on social media – a survey
ABSTRACT Social media following its introduction has witnessed a lot of scholarly attention in recent years due to its growing popularity. These various social media sites have become the mecca of information because of their less costly and easy accessibility. Although these sites were developed to enhance our lives, they are seen as both angelic and vicious. Growing misinformation and fake content by malicious users have not only plagued our online social media ecosystem into chaos, but it also meted untold suffering to humankind. Recently, social media has witnessed a reverberation amid the proliferation of fake news which has made people reluctant to engage in genuine news sharing for fear that such information is false. Consequently, there is a dire need for these fake content to be detected and removed from social media. This study explores the various methods of combating fake news on social media such as Natural Language Processing, Hybrid model. We surmised that detecting fake news is a challenging and complex issue, however, it remains a workable task. Revelation in this study holds that the application of hybrid-machine learning techniques and the collective effort of humans could stand a higher chance of fighting misinformation on social media.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.50
自引率
0.00%
发文量
18
审稿时长
27 weeks
期刊最新文献
A fast and efficient data reuse scheme for HEVC Integer Motion Estimation hardware architecture 2TierEdge-Defense: a cascaded defense framework with rule-based LSTM for NCIFA in NDN Physical layer security in wireless sensors networks: secrecy outage probability analysis Deep learning-based human pose estimation towards artworks classification JCARP: Joint Channel Assignment and Routing Protocol for cognitive-radio-based internet of things (CRIoT)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1