Thai Clickbait Headline News Classification and its Characteristic

Natnicha Wongsap, Tastanya Prapphan, Lisha Lou, S. Kongyoung, Sasiwimol Jumun, Natsuda Kaothanthong
{"title":"Thai Clickbait Headline News Classification and its Characteristic","authors":"Natnicha Wongsap, Tastanya Prapphan, Lisha Lou, S. Kongyoung, Sasiwimol Jumun, Natsuda Kaothanthong","doi":"10.1109/ICESIT-ICICTES.2018.8442064","DOIUrl":null,"url":null,"abstract":"Clickbait is a widely used writing style of the news headline that has been utilized to gain attentions from the reader for the revenues generated from the clicks. After the readers open the link to read the content of the clickbait headline, it leaves them a disappointment. In this work, the characteristic of Thai clickbait headlines is studied. To compare the effect of the special characters such as ‘!’, ‘?’, and ‘#’ on the classification, two datasets, which contains the special characters and the one without them, are provided. They have been utilized in the experiments using well-known classifiers such as Decision Tree, Support Vector Machine, and Naive Bayes. The result shows that the special characters and the decision tree classifier gives 99. 90% accuracy.","PeriodicalId":57136,"journal":{"name":"单片机与嵌入式系统应用","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"单片机与嵌入式系统应用","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/ICESIT-ICICTES.2018.8442064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Clickbait is a widely used writing style of the news headline that has been utilized to gain attentions from the reader for the revenues generated from the clicks. After the readers open the link to read the content of the clickbait headline, it leaves them a disappointment. In this work, the characteristic of Thai clickbait headlines is studied. To compare the effect of the special characters such as ‘!’, ‘?’, and ‘#’ on the classification, two datasets, which contains the special characters and the one without them, are provided. They have been utilized in the experiments using well-known classifiers such as Decision Tree, Support Vector Machine, and Naive Bayes. The result shows that the special characters and the decision tree classifier gives 99. 90% accuracy.
泰国标题党新闻分类及其特点
标题党(Clickbait)是一种广泛使用的新闻标题写作风格,它被用来吸引读者的注意力,以获得点击带来的收入。当读者打开链接阅读标题党标题的内容后,他们会感到失望。在这项工作中,研究泰国标题党标题的特点。为了比较特殊字符(如' !“,”?,和分类上的“#”,提供两个数据集,一个包含特殊字符,一个不包含特殊字符。它们已经在实验中使用了众所周知的分类器,如决策树、支持向量机和朴素贝叶斯。结果表明,特殊字符和决策树分类器给出了99。90%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
7395
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信