Vaporous Marketing: Uncovering Pervasive Electronic Cigarette Advertisements on Twitter

被引:47
作者
Clark, Eric M. [1 ,2 ,3 ,4 ]
Jones, Chris A. [4 ,5 ,6 ]
Williams, Jake Ryland [2 ,3 ,7 ]
Kurti, Allison N. [5 ]
Norotsky, Mitchell Craig [4 ]
Danforth, Christopher M. [1 ,2 ,3 ]
Dodds, Peter Sheridan [1 ,2 ,3 ]
机构
[1] Univ Vermont, Dept Math & Stat, Burlington, VT 05405 USA
[2] Computat Story Lab, Burlington, VT USA
[3] Univ Vermont, Ctr Complex Syst, Burlington, VT USA
[4] Univ Vermont, Dept Surg, Burlington, VT 05405 USA
[5] Univ Vermont, Vermont Ctr Behav & Hlth, Burlington, VT USA
[6] Univ Vermont, Vermont Ctr Clin & Translat Sci, Global Hlth Econ Unit, Burlington, VT USA
[7] Univ Calif Berkeley, Sch Informat, Berkeley, CA 94720 USA
来源
PLOS ONE | 2016年 / 11卷 / 07期
关键词
NICOTINE DELIVERY-SYSTEMS; AWARENESS;
D O I
10.1371/journal.pone.0157304
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Twitter has become the "wild-west" of marketing and promotional strategies for advertisement agencies. Electronic cigarettes have been heavily marketed across Twitter feeds, offering discounts, "kid-friendly" flavors, algorithmically generated false testimonials, and free samples. Methods All electronic cigarette keyword related tweets from a 10% sample of Twitter spanning January 2012 through December 2014 (approximately 850,000 total tweets) were identified and categorized as Automated or Organic by combining a keyword classification and a machine trained Human Detection algorithm. A sentiment analysis using Hedonometrics was performed on Organic tweets to quantify the change in consumer sentiments over time. Commercialized tweets were topically categorized with key phrasal pattern matching. Results The overwhelming majority (80%) of tweets were classified as automated or promotional in nature. The majority of these tweets were coded as commercialized (83.65% in 2013), up to 33% of which offered discounts or free samples and appeared on over a billion twitter feeds as impressions. The positivity of Organic (human) classified tweets has decreased over time (5.84 in 2013 to 5.77 in 2014) due to a relative increase in the negative words 'ban', 'tobacco', 'doesn't', 'drug', 'against', 'poison', 'tax' and a relative decrease in the positive words like 'haha', 'good', 'cool'. Automated tweets are more positive than organic (6.17 versus 5.84) due to a relative increase in the marketing words like 'best', 'win', 'buy', 'sale', 'ealth', 'discount' and a relative decrease in negative words like 'bad', 'hate', 'stupid', 'don't'. Conclusions Due to the youth presence on Twitter and the clinical uncertainty of the long term health complications of electronic cigarette consumption, the protection of public health warrants scrutiny and potential regulation of social media marketing.
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