在多语言假新闻中寻找共同特征:一种定量聚类方法

IF 0.7 3区 文学 0 HUMANITIES, MULTIDISCIPLINARY Digital Scholarship in the Humanities Pub Date : 2024-04-03 DOI:10.1093/llc/fqae016
Wei Yuan, Haitao Liu
{"title":"在多语言假新闻中寻找共同特征:一种定量聚类方法","authors":"Wei Yuan, Haitao Liu","doi":"10.1093/llc/fqae016","DOIUrl":null,"url":null,"abstract":"Since the Internet is a breeding ground for unconfirmed fake news, its automatic detection and clustering studies have become crucial. Most current studies focus on English texts, and the common features of multilingual fake news are not sufficiently studied. Therefore, this article uses English, Russian, and Chinese as examples and focuses on identifying the common quantitative features of fake news in different languages at the word, sentence, readability, and sentiment levels. These features are then utilized in principal component analysis, K-means clustering, hierarchical clustering, and two-step clustering experiments, which achieved satisfactory results. The common features we proposed play a greater role in achieving automatic cross-lingual clustering than the features proposed in previous studies. Simultaneously, we discovered a trend toward linguistic simplification and economy in fake news. Furthermore, fake news is easier to understand and uses negative emotional expressions in ways that real news does not. Our research provides new reference features for fake news detection tasks and facilitates research into their linguistic characteristics.","PeriodicalId":45315,"journal":{"name":"Digital Scholarship in the Humanities","volume":"4 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finding common features in multilingual fake news: a quantitative clustering approach\",\"authors\":\"Wei Yuan, Haitao Liu\",\"doi\":\"10.1093/llc/fqae016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the Internet is a breeding ground for unconfirmed fake news, its automatic detection and clustering studies have become crucial. Most current studies focus on English texts, and the common features of multilingual fake news are not sufficiently studied. Therefore, this article uses English, Russian, and Chinese as examples and focuses on identifying the common quantitative features of fake news in different languages at the word, sentence, readability, and sentiment levels. These features are then utilized in principal component analysis, K-means clustering, hierarchical clustering, and two-step clustering experiments, which achieved satisfactory results. The common features we proposed play a greater role in achieving automatic cross-lingual clustering than the features proposed in previous studies. Simultaneously, we discovered a trend toward linguistic simplification and economy in fake news. Furthermore, fake news is easier to understand and uses negative emotional expressions in ways that real news does not. Our research provides new reference features for fake news detection tasks and facilitates research into their linguistic characteristics.\",\"PeriodicalId\":45315,\"journal\":{\"name\":\"Digital Scholarship in the Humanities\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2024-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digital Scholarship in the Humanities\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1093/llc/fqae016\",\"RegionNum\":3,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"HUMANITIES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Scholarship in the Humanities","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1093/llc/fqae016","RegionNum":3,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"HUMANITIES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

互联网是未经证实的假新闻的温床,因此对其进行自动检测和聚类研究变得至关重要。目前的研究大多集中在英文文本上,而对多语言假新闻的共同特征研究不足。因此,本文以英文、俄文和中文为例,重点从词、句、可读性和情感层面识别不同语言假新闻的共同量化特征。然后利用这些特征进行主成分分析、K-均值聚类、层次聚类和两步聚类实验,取得了令人满意的结果。与以往研究中提出的特征相比,我们提出的共同特征在实现跨语言自动聚类方面发挥了更大的作用。同时,我们发现假新闻在语言上有简化和经济的趋势。此外,假新闻更容易理解,并且使用了负面情绪表达方式,而真实新闻则没有。我们的研究为假新闻检测任务提供了新的参考特征,并促进了对其语言特点的研究。
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
Finding common features in multilingual fake news: a quantitative clustering approach
Since the Internet is a breeding ground for unconfirmed fake news, its automatic detection and clustering studies have become crucial. Most current studies focus on English texts, and the common features of multilingual fake news are not sufficiently studied. Therefore, this article uses English, Russian, and Chinese as examples and focuses on identifying the common quantitative features of fake news in different languages at the word, sentence, readability, and sentiment levels. These features are then utilized in principal component analysis, K-means clustering, hierarchical clustering, and two-step clustering experiments, which achieved satisfactory results. The common features we proposed play a greater role in achieving automatic cross-lingual clustering than the features proposed in previous studies. Simultaneously, we discovered a trend toward linguistic simplification and economy in fake news. Furthermore, fake news is easier to understand and uses negative emotional expressions in ways that real news does not. Our research provides new reference features for fake news detection tasks and facilitates research into their linguistic characteristics.
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
1.80
自引率
25.00%
发文量
78
期刊介绍: DSH or Digital Scholarship in the Humanities is an international, peer reviewed journal which publishes original contributions on all aspects of digital scholarship in the Humanities including, but not limited to, the field of what is currently called the Digital Humanities. Long and short papers report on theoretical, methodological, experimental, and applied research and include results of research projects, descriptions and evaluations of tools, techniques, and methodologies, and reports on work in progress. DSH also publishes reviews of books and resources. Digital Scholarship in the Humanities was previously known as Literary and Linguistic Computing.
期刊最新文献
Social network analysis of the Babylonian Talmud Ancient classical theatre from the digital humanities: a systematic review 2010–21 Language-based machine perception: linguistic perspectives on the compilation of captioning datasets Personality prediction via multi-task transformer architecture combined with image aesthetics Who wrote the first Constitutions of Freemasonry?
×
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