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arXiv · 1905.00075

On the Use of ArXiv as a Dataset

Colin B. Clement·Matthew Bierbaum·Kevin P. O'Keeffe·Alexander A. Alemi
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Abstract

The arXiv has collected 1.5 million pre-print articles over 28 years, hosting literature from scientific fields including Physics, Mathematics, and Computer Science. Each pre-print features text, figures, authors, citations, categories, and other metadata. These rich, multi-modal features, combined with the natural graph structure---created by citation, affiliation, and co-authorship---makes the arXiv an exciting candidate for benchmarking next-generation models. Here we take the first necessary steps toward this goal, by providing a pipeline which standardizes and simplifies access to the arXiv's publicly available data. We use this pipeline to extract and analyze a 6.7 million edge citation graph, with an 11 billion word corpus of full-text research articles. We present some baseline classification results, and motivate application of more exciting generative graph models.

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Colin B. Clement, Matthew Bierbaum, Kevin P. O'Keeffe, Alexander A. Alemi. 2019-04-30. On the Use of ArXiv as a Dataset. https://arxiv.org/abs/1905.00075

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