New dataset enables large-scale analysis of scientific paper structure

Researchers have created a large-scale dataset for automatically classifying rhetorical sections within scientific papers. This dataset, derived from millions of papers in the Semantic Scholar Open Research Corpus (S2ORC), uses a rule-based algorithm to label sections like Introduction, Methods, Results, and Discussion. Validation studies indicate that the automated classification achieves agreement levels comparable to human annotators, making it suitable for large-scale computational analysis of scientific writing. AI

IMPACT Enables new avenues for computational linguistics research and analysis of scientific discourse.

RANK_REASON The cluster describes a new dataset for classifying rhetorical sections in scientific papers, which is a research artifact. [lever_c_demoted from research: ic=1 ai=0.7]

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• arXiv
• Jacob Aarup Dalsgaard
• Semantic Scholar Open Research Corpus

• paper
• other

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