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Identifying Topics for E-Cigarette User-Generated Contents: A Case Study From Multiple Social Media Platforms

机译:识别电子烟用户生成内容的主题:来自多个社交媒体平台的案例研究

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Background: Electronic cigarette (e-cigarette) is an emerging product with a rapid-growth market in recent years. Social media has become an important platform for information seeking and sharing. We aim to mine hidden topics from e-cigarette datasets collected from different social media platforms.Objective: This paper aims to gain a systematic understanding of the characteristics of various types of social media, which will provide deep insights into how consumers and policy makers effectively use social media to track e-cigarette-related content and adjust their decisions and policies.Methods: We collected data from Reddit (27,638 e-cigarette flavor-related posts from January 1, 2011, to June 30, 2015), JuiceDB (14,433 e-juice reviews from June 26, 2013 to November 12, 2015), and Twitter (13,356 “e-cig ban”-related tweets from January, 1, 2010 to June 30, 2015). Latent Dirichlet Allocation, a generative model for topic modeling, was used to analyze the topics from these data.Results: We found four types of topics across the platforms: (1) promotions, (2) flavor discussions, (3) experience sharing, and (4) regulation debates. Promotions included sales from vendors to users, as well as trades among users. A total of 10.72% (2,962/27,638) of the posts from Reddit were related to trading. Promotion links were found between social media platforms. Most of the links (87.30%) in JuiceDB were related to Reddit posts. JuiceDB and Reddit identified consistent flavor categories. E-cigarette vaping methods and features such as steeping, throat hit, and vapor production were broadly discussed both on Reddit and on JuiceDB. Reddit provided space for policy discussions and majority of the posts (60.7%) holding a negative attitude toward regulations, whereas Twitter was used to launch campaigns using certain hashtags. Our findings are based on data across different platforms. The topic distribution between Reddit and JuiceDB was significantly different (P<.001), which indicated that the user discussions focused on different perspectives across the platforms.Conclusions: This study examined Reddit, JuiceDB, and Twitter as social media data sources for e-cigarette research. These mined findings could be further used by other researchers and policy makers. By utilizing the automatic topic-modeling method, the proposed unified feedback model could be a useful tool for policy makers to comprehensively consider how to collect valuable feedback from social media.
机译:背景:电子烟(电子烟)是近年来发展迅速的新兴产品。社交媒体已经成为寻求和共享信息的重要平台。我们旨在从不同社交媒体平台收集的电子烟数据集中挖掘隐藏的话题。目的:本文旨在系统地了解各种社交媒体的特征,从而为消费者和政策制定者如何有效地提供深刻的见解。方法:我们收集了Reddit(2011年1月1日至2015年6月30日,共27,638个与电子烟风味相关的帖子),JuiceDB(14,433)的数据从2013年6月26日至2015年11月12日的电子果汁评论)和Twitter(从2010年1月1日至2015年6月30日的13356条“电子烟禁令”相关推文)。结果:我们在平台上发现了四种类型的主题:(1)促销,(2)风味讨论,(3)经验分享, (4)法规辩论。促销包括从供应商到用户的销售以及用户之间的交易。 Reddit的职位总数中有10.72%(2,962 / 27,638)与交易有关。在社交媒体平台之间发现了促销链接。 JuiceDB中的大多数链接(87.30%)与Reddit帖子有关。 JuiceDB和Reddit确定了一致的风味类别。在Reddit和JuiceDB上都广泛讨论了电子烟的抽烟方法和功能,例如浸泡,喉咙撞击和蒸汽产生。 Reddit为政策讨论提供了空间,大多数帖子(60.7%)对法规持消极态度,而Twitter被用于使用某些主题标签发起活动。我们的发现基于不同平台上的数据。 Reddit与JuiceDB之间的主题分布存在显着差异(P <.001),这表明用户讨论侧重于跨平台的不同观点。结论:本研究研究了Reddit,JuiceDB和Twitter作为e-社交媒体数据源香烟研究。这些发现的结果可能会被其他研究人员和政策制定者进一步使用。通过使用自动主题建模方法,所提出的统一反馈模型可以成为决策者全面考虑如何从社交媒体收集有价值的反馈的有用工具。

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