  This paper studies the dynamics of opinion formation and polarization in
social media. We investigate whether users' stance concerning contentious
subjects is influenced by the online discussions they are exposed to and
interactions with users supporting different stances. We set up a series of
predictive exercises based on machine learning models. Users are described
using several posting activities features capturing their overall activity
levels, posting success, the reactions their posts attract from users of
different stances, and the types of discussions in which they engage. Given the
user description at present, the purpose is to predict their stance in the
future. Using a dataset of Brexit discussions on the Reddit platform, we show
that the activity features regularly outperform the textual baseline,
confirming the link between exposure to discussion and opinion. We find that
the most informative features relate to the stance composition of the
discussion in which users prefer to engage.
