Public reactions to e-cigarette regulations on Twitter: a text mining analysis

Tob Control. 2017 Dec;26(e2):e112-e116. doi: 10.1136/tobaccocontrol-2016-053295. Epub 2017 Mar 24.

Abstract

Background: In May 2016, the Food and Drug Administration (FDA) issued a final rule that deemed e-cigarettes to be within their regulatory authority as a tobacco product. News and opinions about the regulation were shared on social media platforms, such as Twitter, which can play an important role in shaping the public's attitudes. We analysed information shared on Twitter for insights into initial public reactions.

Methods: A text mining approach was used to uncover important topics among reactions to the e-cigarette regulations on Twitter. SAS Text Miner V.12.1 software was used for descriptive text mining to uncover the primary topics from tweets collected from May 1 to May 17 2016 using NUVI software to gather the data.

Results: A total of nine topics were generated. These topics reveal initial reactions to whether the FDA's e-cigarette regulations will benefit or harm public health, how the regulations will impact the emerging e-cigarette market and efforts to share the news. The topics were dominated by negative or mixed reactions.

Conclusions: In the days following the FDA's announcement of the new deeming regulations, the public reaction on Twitter was largely negative. Public health advocates should consider using social media outlets to better communicate the policy's intentions, reach and potential impact for public good to create a more balanced conversation.

Keywords: Electronic nicotine delivery devices; Media; Public opinion.

MeSH terms

  • Data Mining
  • Electronic Nicotine Delivery Systems*
  • Government Regulation
  • Humans
  • Public Health
  • Public Opinion*
  • Social Media / statistics & numerical data*
  • Tobacco Products / legislation & jurisprudence*
  • United States
  • United States Food and Drug Administration