{"title":"作为点击诱饵的官方统计——后真相社会的新威胁？","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":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\":null,\"pages\":null},\"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}","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}
Official Statistics as Clickbait—The New Threat in the Post-truth Society?
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.
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