  Leveraging social media data to understand people's lifestyle choices is an
exciting domain to explore but requires a multiview formulation of the data. In
this paper, we propose a joint embedding model based on the fusion of neural
networks with attention mechanism by incorporating social and textual
information of users to understand their activities and motivations. We use
well-being related tweets from Twitter, focusing on 'Yoga'. We demonstrate our
model on two downstream tasks: (i) finding user type such as either
practitioner or promotional (promoting yoga studio/gym), other; (ii) finding
user motivation i.e. health benefit, spirituality, love to tweet/retweet about
yoga but do not practice yoga.
