Do You Do Yoga? Understanding Twitter Users' Types and Motivations using Social and Textual Information
arXiv:2012.09332 · doi:10.1109/ICSC50631.2021.00067
Abstract
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.
accepted at 2021 IEEE 15th International Conference on Semantic Computing (ICSC), 4 pages. Minor changes for camera-ready version. arXiv admin note: text overlap with arXiv:2012.02939