Influence and Its Detection with Lexomic Analysis
Michael D. C. Drout · Palgrave Macmillan US eBooks · 2013
This chapter 1 introduces computer-aided, statistical methods for detecting influence. These approaches, which we call “lexomics,” were originally developed for the analysis of biological relationships, but our research group at Wheaton College has modified them for the analysis of literary texts. 2 Lexomic methods are successful at identifying influence because the similarity between memes and genes is not just a powerful and useful metaphor but also a recognition of the identity of the fundamental underlying processes of the differential reproduction of replicating entities. It has therefore been possible to take techniques designed for the analysis of genes and apply them to the analysis of memes. Using these methods, as well as traditional philological approaches to cultural analysis, I will in this chapter show the specific ways particular literary texts have evolved and been influenced and how memes remain stable in some ways and change in others as they cross particular boundaries from one culture or language to another. Lexomic methods allow us to identify memes, to see their influence on other memes, and to find their traces where they otherwise might not be noticed. The goal of this chapter is not only to present the methods and show that they work but also to explain what their working illustrates about cultural evolution. It turns out that the meme-based theory of culture is the best available explanation for the phenomena uncovered by lexomic methods and that lexomic methods give us greater insight into the evolution of meme-plexes. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.