Twitter 上电子烟营销和非营销主题的探索性分析。

Sifei Han, Ramakanth Kavuluru
{"title":"Twitter 上电子烟营销和非营销主题的探索性分析。","authors":"Sifei Han, Ramakanth Kavuluru","doi":"10.1007/978-3-319-47874-6_22","DOIUrl":null,"url":null,"abstract":"<p><p>Electronic cigarettes (e-cigs) have been gaining popularity and have emerged as a controversial tobacco product since their introduction in 2007 in the U.S. The smoke-free aspect of e-cigs renders them less harmful than conventional cigarettes and is one of the main reasons for their use by people who plan to quit smoking. The US food and drug administration (FDA) has introduced new regulations early May 2016 that went into effect on August 8, 2016. Given this important context, in this paper, we report results of a project to identify current <i>themes</i> in e-cig tweets in terms of semantic interpretations of topics generated with topic modeling. Given marketing/advertising tweets constitute almost half of all e-cig tweets, we first build a classifier that identifies marketing and non-marketing tweets based on a hand-built dataset of 1000 tweets. After applying the classifier to a dataset of over a million tweets (collected during 4/2015 - 6/2016), we conduct a preliminary content analysis and run topic models on the two sets of tweets separately after identifying the appropriate numbers of topics using <i>topic coherence.</i> We interpret the results of the topic modeling process by relating topics generated to specific e-cig themes. We also report on themes identified from e-cig tweets generated at particular places (such as schools and churches) for geo-tagged tweets found in our dataset using the GeoNames API. To our knowledge, this is the first effort that employs topic modeling to identify e-cig themes in general and in the context of geo-tagged tweets tied to specific places of interest.</p>","PeriodicalId":92139,"journal":{"name":"Social informatics : 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11-14, 2016, Proceedings. Part II. SocInfo (Conference) (8th : 2016 : Bellevue, Wash.)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540097/pdf/nihms877770.pdf","citationCount":"0","resultStr":"{\"title\":\"Exploratory Analysis of Marketing and Non-marketing E-cigarette Themes on Twitter.\",\"authors\":\"Sifei Han, Ramakanth Kavuluru\",\"doi\":\"10.1007/978-3-319-47874-6_22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Electronic cigarettes (e-cigs) have been gaining popularity and have emerged as a controversial tobacco product since their introduction in 2007 in the U.S. The smoke-free aspect of e-cigs renders them less harmful than conventional cigarettes and is one of the main reasons for their use by people who plan to quit smoking. The US food and drug administration (FDA) has introduced new regulations early May 2016 that went into effect on August 8, 2016. Given this important context, in this paper, we report results of a project to identify current <i>themes</i> in e-cig tweets in terms of semantic interpretations of topics generated with topic modeling. Given marketing/advertising tweets constitute almost half of all e-cig tweets, we first build a classifier that identifies marketing and non-marketing tweets based on a hand-built dataset of 1000 tweets. After applying the classifier to a dataset of over a million tweets (collected during 4/2015 - 6/2016), we conduct a preliminary content analysis and run topic models on the two sets of tweets separately after identifying the appropriate numbers of topics using <i>topic coherence.</i> We interpret the results of the topic modeling process by relating topics generated to specific e-cig themes. We also report on themes identified from e-cig tweets generated at particular places (such as schools and churches) for geo-tagged tweets found in our dataset using the GeoNames API. To our knowledge, this is the first effort that employs topic modeling to identify e-cig themes in general and in the context of geo-tagged tweets tied to specific places of interest.</p>\",\"PeriodicalId\":92139,\"journal\":{\"name\":\"Social informatics : 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11-14, 2016, Proceedings. Part II. SocInfo (Conference) (8th : 2016 : Bellevue, Wash.)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540097/pdf/nihms877770.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Social informatics : 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11-14, 2016, Proceedings. Part II. SocInfo (Conference) (8th : 2016 : Bellevue, Wash.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/978-3-319-47874-6_22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2016/10/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social informatics : 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11-14, 2016, Proceedings. Part II. SocInfo (Conference) (8th : 2016 : Bellevue, Wash.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-319-47874-6_22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/10/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

电子香烟(e-cigs)自 2007 年在美国推出以来,受到越来越多人的欢迎,并成为一种备受争议的烟草产品。电子香烟的无烟特性使其危害低于传统香烟,这也是计划戒烟的人使用电子香烟的主要原因之一。美国食品和药物管理局(FDA)于2016年5月初出台了新法规,并于2016年8月8日正式生效。鉴于这一重要背景,我们在本文中报告了一个项目的成果,该项目旨在通过对主题建模生成的主题进行语义解释来识别电子烟推文中的当前主题。鉴于营销/广告推文几乎占了所有电子烟推文的一半,我们首先根据手工建立的 1000 条推文数据集建立了一个分类器,用于识别营销和非营销推文。在将分类器应用于超过 100 万条推文(收集于 2015 年 4 月至 2016 年 6 月)的数据集后,我们进行了初步的内容分析,并在使用主题一致性识别出适当数量的主题后,分别对两组推文运行主题模型。我们将生成的话题与特定的电子烟主题联系起来,从而解释话题建模过程的结果。我们还报告了从特定地点(如学校和教堂)产生的电子烟推文中识别出的主题,这些推文是使用 GeoNames API 在数据集中找到的带有地理标记的推文。据我们所知,这是首次采用主题建模来识别一般电子烟主题以及与特定兴趣场所相关的地理标记推文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Exploratory Analysis of Marketing and Non-marketing E-cigarette Themes on Twitter.

Electronic cigarettes (e-cigs) have been gaining popularity and have emerged as a controversial tobacco product since their introduction in 2007 in the U.S. The smoke-free aspect of e-cigs renders them less harmful than conventional cigarettes and is one of the main reasons for their use by people who plan to quit smoking. The US food and drug administration (FDA) has introduced new regulations early May 2016 that went into effect on August 8, 2016. Given this important context, in this paper, we report results of a project to identify current themes in e-cig tweets in terms of semantic interpretations of topics generated with topic modeling. Given marketing/advertising tweets constitute almost half of all e-cig tweets, we first build a classifier that identifies marketing and non-marketing tweets based on a hand-built dataset of 1000 tweets. After applying the classifier to a dataset of over a million tweets (collected during 4/2015 - 6/2016), we conduct a preliminary content analysis and run topic models on the two sets of tweets separately after identifying the appropriate numbers of topics using topic coherence. We interpret the results of the topic modeling process by relating topics generated to specific e-cig themes. We also report on themes identified from e-cig tweets generated at particular places (such as schools and churches) for geo-tagged tweets found in our dataset using the GeoNames API. To our knowledge, this is the first effort that employs topic modeling to identify e-cig themes in general and in the context of geo-tagged tweets tied to specific places of interest.

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
期刊最新文献
Exploratory Analysis of Marketing and Non-marketing E-cigarette Themes on Twitter.
×
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