Abstract

We analyze the ACL Anthology citation network in an attempt to identify the most “central ” papers and authors using graph-based methods. Citation data was obtained using text extraction from the library of PDF files with some post-processing performed to clean up the results. Manual annotation of the references was then performed to complete the citation network. The analysis compares metrics across publication years and venues, such as citations in and out. The most cited paper, central papers, and papers with the highest impact factor are also established. 1

Citations