An Ecology of Text: Using Text Retrieval to Study Alife on the Net

Abstract

I introduce a new alife model, an ecology based on a corpus of text, and apply it to the analysis of posts to USENET News. In this corporal ecology posts are organisms, the newsgroups of NetNews define an environment, and human posters situated in their wider context make up a scarce resource. I apply latent semantic indexing (LSI), a text retrieval method based on principal component analysis, to distill from the corpus those replicating units of text. LSI arrives at suitable replicators because it discovers word co-occurrences that segregate and recombine with appreciable frequency. I argue that natural selection is necessarily in operation because sufficient conditions for its occurrence are met: replication, mutagenicity, and trait/fitness covariance. I describe a set of experiments performed on a static corpus of over 10,000 posts. In these experiments I study average population fitness, a fundamental element of population ecology. My study of fitness arrives at the tinhappy discovery that a flame-war, centered around an overly prolific poster, is the king of the jungle.