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".

本研究使用Granger因果关系探究社交媒体中瑜伽与快乐之间的关系，结合文本和时间信息，通过内容分析衡量瑜伽活动水平和快乐情绪，并使用神经网络和注意力机制提出联合嵌入模型以了解用户瑜伽活动，利用注意力神经网络模型和迁移学习方法测量用户快乐情绪，Twitter数据实验表明，有1447个用户在瑜伽活动时“瑜伽Granger导致快乐”。

瑜伽是否让你快乐？利用文本和时间信息分析推特用户的幸福感