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論文資訊
- 類型：已發表論文
- 日期：2017-03-01
摘要
The reasons for using electronic nicotine delivery systems (ENDS) are p oorly understood and are primarily documented by expensive cross-sectional surveys that use preconceived close-ended response options rather than allowing respondents to use their own words. We passively identify the reasons for using ENDS longitudinally from a content analysis of public postings on Twitter. All English 語言 public tweets including several ENDS terms (e.g., "e-cigarette" or "vape") were captured from the Twitter data stream during 2012 and 2015. After excluding spam, advertisements, and retweets, posts indicating a rationale for vaping were retained. The specific reasons for vaping were then inferred based on a supervised content analysis using annotators from Amazon's Mechanical Turk. During 2012 quitti
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