Does Size Matter? Authorship Attribution, Small Samples, Big Problem

Abstract

The aim of this study is to find a minimal size of text samples for authorship attribution that would provide stable results independent of random noise. A few controlled tests for different sample lengths, languages and genres are discussed and compared. Although I focus on Delta methodology, the results are valid for many other multidimensional methods relying on word frequencies and nearest neighbor classifications.