Huang Jidong, Kornfield Rachel, Szczypka Glen, Emery Sherry L
Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois, USA.
Tob Control. 2014 Jul;23 Suppl 3(Suppl 3):iii26-30. doi: 10.1136/tobaccocontrol-2014-051551.
Rapid increases in marketing of e-cigarettes coincide with growth in e-cigarette use in recent years; however, little is known about how e-cigarettes are marketed on social media platforms.
Keywords were used to collect tweets related to e-cigarettes from the Twitter Firehose between 1 May 2012 and 30 June 2012. Tweets were coded for smoking cessation mentions, as well as health and safety mentions, and were classified as commercial or non-commercial ('organic') tweets using a combination of Naïve Bayes machine learning methods, keyword algorithms and human coding. Metadata associated with each tweet were used to examine the characteristics of accounts tweeting about e-cigarettes.
73,672 tweets related to e-cigarettes were captured in the study period, 90% of which were classified as commercial tweets. Accounts tweeting commercial e-cigarette content were associated with lower Klout scores, a measure of influence. Commercial tweeting was largely driven by a small group of highly active accounts, and 94% of commercial tweets included links to websites, many of which sell or promote e-cigarettes. Approximately 10% of commercial and organic tweets mentioned smoking cessation, and 34% of commercial tweets included mentions of prices or discounts for e-cigarettes.
Twitter appears to be an important marketing platform for e-cigarettes. Tweets related to e-cigarettes were overwhelmingly commercial, and a substantial proportion mentioned smoking cessation. E-cigarette marketing on Twitter may have public health implications. Continued surveillance of e-cigarette marketing on social media platforms is needed.
近年来,电子烟营销的快速增长与电子烟使用的增加相吻合;然而,对于电子烟在社交媒体平台上如何进行营销却知之甚少。
使用关键词从2012年5月1日至2012年6月30日的Twitter Firehose中收集与电子烟相关的推文。对推文进行编码,以确定是否提及戒烟以及健康与安全方面的内容,并结合朴素贝叶斯机器学习方法、关键词算法和人工编码,将其分类为商业或非商业(“自然”)推文。与每条推文相关的元数据用于检查发布关于电子烟推文的账户特征。
在研究期间共捕获了73672条与电子烟相关的推文,其中90%被分类为商业推文。发布商业电子烟内容的账户与较低的Klout得分(一种影响力衡量指标)相关。商业推文主要由一小部分高活跃度账户推动,94%的商业推文包含网站链接,其中许多网站销售或推广电子烟。大约10%的商业和自然推文提到了戒烟,34%的商业推文包含电子烟价格或折扣的提及。
Twitter似乎是电子烟的一个重要营销平台。与电子烟相关的推文绝大多数是商业性质的,且相当一部分提到了戒烟。在Twitter上进行的电子烟营销可能对公众健康有影响。需要持续监测社交媒体平台上的电子烟营销情况。