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这是谁的帖子?从社交媒体帖子中预测电子烟品牌。

Whose Post Is It? Predicting E-cigarette Brand from Social Media Posts.

作者信息

Vandewater Elizabeth A, Clendennen Stephanie L, Hébert Emily T, Bigman Galya, Jackson Christian D, Wilkinson Anna V, Perry Cheryl L

机构信息

Director of Data Science and Research Services, The University of Texas at Austin, Population Research Center, Austin, TX.

Predoctoral Fellow, UTHealth School of Public Health in Austin, TX.

出版信息

Tob Regul Sci. 2018 Mar;4(2):30-43. doi: 10.18001/TRS.4.2.3.

Abstract

OBJECTIVES

E-cigarette advertisers know that 76% of youth use social media, yet little is known about the nature of e-cigarette advertising on social media most favored by youth. We utilized text-mining to characterize e-cigarette advertising and marketing messages from image-focused social media brand sites, and to construct and test an algorithm for predicting brand from brand-generated social media posts.

METHODS

Data comprised 5022 unique posts accompanied by an image from Facebook, Instagram or Pinterest e-cigarette brand pages for Blu, Logic, Metro, and NJOY from February 2012 to April 2015. Text-tokenization was used to quantify text for use as predictors in analyses.

RESULTS

Blu had the largest social media presence (65%), followed by Logic (16%), NJOY (12%) and Metro (7%). Blu's average post length was significantly shorter than all other brands. Words most commonly used in posts differed by brand. Regression analyses successfully differentiated Blu and NJOY brands from other brands.

CONCLUSIONS

Analyses revealed e-cigarette brands used different types of messages to appeal to social media users. Whereas words used by Blu and NJOY sold a "lifestyle," words used by Logic and Metro relied on device and product identification.

摘要

目标

电子烟广告商知道76%的年轻人使用社交媒体,但对于在年轻人最青睐的社交媒体上电子烟广告的性质却知之甚少。我们利用文本挖掘来描述来自以图像为主的社交媒体品牌网站的电子烟广告和营销信息,并构建和测试一种从品牌生成的社交媒体帖子中预测品牌的算法。

方法

数据包括2012年2月至2015年4月期间来自Facebook、Instagram或Pinterest上Blu、Logic、Metro和NJOY电子烟品牌页面的5022条带有图像的独特帖子。文本分词用于量化文本,以便在分析中用作预测指标。

结果

Blu在社交媒体上的活跃度最高(65%),其次是Logic(16%)、NJOY(12%)和Metro(7%)。Blu的平均帖子长度明显短于所有其他品牌。不同品牌帖子中最常用的词汇也有所不同。回归分析成功地将Blu和NJOY品牌与其他品牌区分开来。

结论

分析表明,电子烟品牌使用不同类型的信息来吸引社交媒体用户。Blu和NJOY使用的词汇推销的是一种“生活方式”,而Logic和Metro使用的词汇则依赖于设备和产品识别。

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