Official Statistics as Clickbait—The New Threat in the Post-truth Society?

Lyubomira Dimitrova
{"title":"Official Statistics as Clickbait—The New Threat in the Post-truth Society?","authors":"Lyubomira Dimitrova","doi":"10.17265/2159-5291/2017.03","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to raise awareness on the consequences of dissemination of official statistics through online media that uses clickbait headlines to generate traffic. In order to tackle on this issue, a Natural Language Processing (NLP) model was developed in order to distinguish the clickbait headline from the non-clickbait one when it comes to articles presenting information from the Bulgarian National Statistical Institute press releases. The yielded results are rather satisfactory as the parts-of-speech features model achieved an accuracy for 92% of the cases.","PeriodicalId":61124,"journal":{"name":"数学和系统科学:英文版","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"数学和系统科学:英文版","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.17265/2159-5291/2017.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The aim of this paper is to raise awareness on the consequences of dissemination of official statistics through online media that uses clickbait headlines to generate traffic. In order to tackle on this issue, a Natural Language Processing (NLP) model was developed in order to distinguish the clickbait headline from the non-clickbait one when it comes to articles presenting information from the Bulgarian National Statistical Institute press releases. The yielded results are rather satisfactory as the parts-of-speech features model achieved an accuracy for 92% of the cases.
作为点击诱饵的官方统计——后真相社会的新威胁?
本文的目的是提高人们对通过使用点击诱饵标题来产生流量的在线媒体传播官方统计数据的后果的认识。为了解决这个问题,开发了一个自然语言处理模型,以便在介绍保加利亚国家统计研究所新闻稿信息的文章中区分点击诱饵标题和非点击诱饵标题。所得到的结果相当令人满意,因为词性特征模型在92%的情况下实现了准确率。
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
450
×
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