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Automated 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 truthdoi:10.24963/ijcai.2019/881 dblp:conf/ijcai/PanD19 fatcat:inw55rewvzh5nckevzvrsexwii