  Multiview representation learning of data can help construct coherent and
contextualized users' representations on social media. This paper suggests a
joint embedding model, incorporating users' social and textual information to
learn contextualized user representations used for understanding their
lifestyle choices. We apply our model to tweets related to two lifestyle
activities, `Yoga' and `Keto diet' and use it to analyze users' activity type
and motivation. We explain the data collection and annotation process in detail
and provide an in-depth analysis of users from different classes based on their
Twitter content. Our experiments show that our model results in performance
improvements in both domains.
