  Regulation of tobacco products is rapidly evolving. Understanding public
sentiment in response to changes is very important as authorities assess how to
effectively protect population health. Social media systems are widely
recognized to be useful for collecting data about human preferences and
perceptions. However, how social media data may be used, in rapid policy change
settings, given challenges of narrow time periods and specific locations and
non-representative the population using social media is an open question. In
this paper we apply quasi-experimental designs, which have been used previously
in observational data such as social media, to control for time and location
confounders on social media, and then use content analysis of Twitter and
Reddit posts to illustrate the content of reactions to tobacco flavor bans and
the effect of taxation on e-cigarettes. Conclusions distill the potential role
of social media in settings of rapidly changing regulation, in complement to
what is learned by traditional denominator-based representative surveys.
