Measuring direct and indirect authorial influence in historical corpora

Abstract

We show how automatically extracted citations in historical corpora can be used to measure the direct and indirect influence of authors on each other. These measures can in turn be used to determine an author's overall prominence in the corpus and to identify distinct schools of thought. We apply our methods to two major historical corpora. Using scholarly consensus as a gold standard, we demonstrate empirically the superiority of indirect influence over direct influence as a basis for various measures of authorial impact.