Pan, ShimeiDing, Tao2019-11-142019-11-142019-06Shimei Pan, Tao DingSocial, Media-based User Embedding: A Literature Review, June 2019, https://arxiv.org/abs/1907.00725http://hdl.handle.net/11603/16289Automated representation learning is behind many recent success stories in machine learning. It is often used to transfer knowledge learned from a large dataset (e.g., raw text) to tasks for which only a small number of training examples are available. In this paper, we review recent advance in learning to represent social media users in low-dimensional embeddings. The technology is critical for creating high performance social media-based human traits and behavior models since the ground truth for assessing latent human traits and behavior is often expensive to acquire at a large scale. In this survey, we review typical methods for learning a unified user embeddings from heterogeneous user data (e.g., combines social media texts with images to learn a unified user representation). Finally we point out some current issues and future directions.7 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.machine learningsocial mediauser embeddingbehavior modelshuman traitsText