CLDLNov 4, 2022

SMAuC -- The Scientific Multi-Authorship Corpus

arXiv:2211.02477v22 citationsh-index: 53
AI Analysis

This addresses a data bottleneck for researchers in authorship analysis, though it is incremental as it builds on existing corpus efforts.

The authors tackled the lack of large, metadata-rich datasets for scientific authorship analysis by introducing SMAuC, a corpus with over 3 million publications and 5 million authors, making it the largest openly accessible resource for this purpose.

The rapidly growing volume of scientific publications offers an interesting challenge for research on methods for analyzing the authorship of documents with one or more authors. However, most existing datasets lack scientific documents or the necessary metadata for constructing new experiments and test cases. We introduce SMAuC, a comprehensive, metadata-rich corpus tailored to scientific authorship analysis. Comprising over 3 million publications across various disciplines from over 5 million authors, SMAuC is the largest openly accessible corpus for this purpose. It encompasses scientific texts from humanities and natural sciences, accompanied by extensive, curated metadata, including unambiguous author IDs. SMAuC aims to significantly advance the domain of authorship analysis in scientific texts.

Foundations

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