Burrows‘ Zeta was first suggested by Burrows (2007) and was used originally for stylometric Authorship Attribution. There are several variants of Zeta proposed by Craig and Kinney (2009) and by Schöch et al. (2018). Zeta is mathematically very simple and has a bias towards content words, two attributes that make this measure attractive for other application domains in CLS, such as genre analysis (Schöch 2018) or gender analysis (Hoover 2010). This measure quantifies degrees of dispersion of a feature in two corpora and compares them. It is performed by comparing the document proportions of a target word or feature (that is, the proportion of all documents in which the target word occurs at least once) in the target and the comparison corpus. In our framework, we implemented two variants of Zeta: Burrows’ Zeta (Zeta_orig, Burrows 2007) and logarithmic Zeta (Zeta_log, Schöch et al. 2018) to compare their performance. 


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