Neural embeddings of scholarly periodicals reveal complex disciplinary organizations

@article{Peng2021NeuralEO,
  title={Neural embeddings of scholarly periodicals reveal complex disciplinary organizations},
  author={H. Peng and Qing Ke and Ceren Budak and Daniel M. Romero and Yong-Yeol Ahn},
  journal={Science Advances},
  year={2021},
  volume={7}
}
Low-dimensional vector-space representations of academic periodicals reveal insights into their complex relationships. Understanding the structure of knowledge domains is one of the foundational challenges in the science of science. Here, we propose a neural embedding technique that leverages the information contained in the citation network to obtain continuous vector representations of scientific periodicals. We demonstrate that our periodical embeddings encode nuanced relationships between… Expand
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