论文标题
检查自然语言处理文献的引用
Examining Citations of Natural Language Processing Literature
论文作者
论文摘要
我们从ACL选集（AA）和Google Scholar（GS）中提取信息，以检查NLP论文引用的趋势。我们探讨了诸如以下问题：不同类型的论文（期刊文章，会议论文，演示论文等）的引用如何？ NLP内部不同领域的论文的引用如何？值得注意的是，我们表明，AA中只有大约56％的论文被引用了十次或更多次。 CL Journal的论文最多，但近年来其引文主导地位有所下降。平均而言，长篇论文的引文几乎是短论文的三倍。关于情感分类，解剖解决方案和实体识别的论文的中位数最高。此处介绍的分析以及映射到引文的NLP论文的相关数据集具有多种用途，包括：了解该领域如何增长和量化不同类型论文的影响。
We extracted information from the ACL Anthology (AA) and Google Scholar (GS) to examine trends in citations of NLP papers. We explore questions such as: how well cited are papers of different types (journal articles, conference papers, demo papers, etc.)? how well cited are papers from different areas of within NLP? etc. Notably, we show that only about 56\% of the papers in AA are cited ten or more times. CL Journal has the most cited papers, but its citation dominance has lessened in recent years. On average, long papers get almost three times as many citations as short papers; and papers on sentiment classification, anaphora resolution, and entity recognition have the highest median citations. The analyses presented here, and the associated dataset of NLP papers mapped to citations, have a number of uses including: understanding how the field is growing and quantifying the impact of different types of papers.
