Empirical evaluations of language-based author identification techniques

ABSTRACT Recent Court decisions in the United States call for the empirical testing of language-based author identification techniques. This article shows the results of such testing. The tested hypotheses include: syntactic analysis, syntactically classified punctuation, sentential complexity, vocabulary richness, readability, content analysis, spelling errors, punctuation errors, word form errors, and grammatical errors. These hypotheses are tested on a set of documents written by four women who are similar in age, educational level, and dialectal background: two of the women are Euro-American, and two are Afro-American. Each hypothesis is tested separately to determine its ability to differentiate documents from different authors and cluster doc-uments from each author. Hypotheses which quantify linguistic features are tested statistically using the chi-square statistic. Discrimination error rates are calculated. Only two hypotheses successfully differentiate and cluster documents: syntactic analysis and syntactically classified punctuation