通过维基百科页面浏览量估算旅游统计数据

C. Alis, Adrian Letchford, H. S. Moat, T. Preis
{"title":"通过维基百科页面浏览量估算旅游统计数据","authors":"C. Alis, Adrian Letchford, H. S. Moat, T. Preis","doi":"10.1145/2786451.2786925","DOIUrl":null,"url":null,"abstract":"Decision makers depend on socio-economic indicators to shape the world we inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Our increasing interactions with large scale technological systems are generating vast datasets on global human behaviour which are immediately accessible. Here we analyse whether data on how often people view Wikipedia articles might help us to improve estimates of the current number of tourists leaving the UK. Our analyses suggest that in the absence of sufficient history, Wikipedia page views provide an advantage. We conclude that when using adaptive models, Wikipedia usage opens up the possibility to improve estimates of tourism demand.","PeriodicalId":93136,"journal":{"name":"Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference","volume":"126 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Estimating tourism statistics with Wikipedia page views\",\"authors\":\"C. Alis, Adrian Letchford, H. S. Moat, T. Preis\",\"doi\":\"10.1145/2786451.2786925\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Decision makers depend on socio-economic indicators to shape the world we inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Our increasing interactions with large scale technological systems are generating vast datasets on global human behaviour which are immediately accessible. Here we analyse whether data on how often people view Wikipedia articles might help us to improve estimates of the current number of tourists leaving the UK. Our analyses suggest that in the absence of sufficient history, Wikipedia page views provide an advantage. We conclude that when using adaptive models, Wikipedia usage opens up the possibility to improve estimates of tourism demand.\",\"PeriodicalId\":93136,\"journal\":{\"name\":\"Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference\",\"volume\":\"126 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2786451.2786925\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2786451.2786925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

决策者依靠社会经济指标来塑造我们居住的世界。由于需要努力收集和汇总基础数据,这些指标的报告往往被推迟。我们与大规模技术系统的互动日益增加,正在产生关于全球人类行为的庞大数据集,这些数据集可以立即访问。在这里,我们分析了人们浏览维基百科文章的频率数据是否可以帮助我们改进对当前离开英国的游客数量的估计。我们的分析表明,在缺乏足够历史的情况下,维基百科的页面浏览量提供了一个优势。我们的结论是,当使用自适应模型时,维基百科的使用打开了改进旅游需求估计的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating tourism statistics with Wikipedia page views
Decision makers depend on socio-economic indicators to shape the world we inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Our increasing interactions with large scale technological systems are generating vast datasets on global human behaviour which are immediately accessible. Here we analyse whether data on how often people view Wikipedia articles might help us to improve estimates of the current number of tourists leaving the UK. Our analyses suggest that in the absence of sufficient history, Wikipedia page views provide an advantage. We conclude that when using adaptive models, Wikipedia usage opens up the possibility to improve estimates of tourism demand.
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
自引率
0.00%
发文量
0
×
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