  Although yoga is a multi-component practice to hone the body and mind and be
known to reduce anxiety and depression, there is still a gap in understanding
people's emotional state related to yoga in social media. In this study, we
investigate the causal relationship between practicing yoga and being happy by
incorporating textual and temporal information of users using Granger
causality. To find out causal features from the text, we measure two variables
(i) Yoga activity level based on content analysis and (ii) Happiness level
based on emotional state. To understand users' yoga activity, we propose a
joint embedding model based on the fusion of neural networks with attention
mechanism by leveraging users' social and textual information. For measuring
the emotional state of yoga users (target domain), we suggest a transfer
learning approach to transfer knowledge from an attention-based neural network
model trained on a source domain. Our experiment on Twitter dataset
demonstrates that there are 1447 users where "yoga Granger-causes happiness".
