A comparison of two text specificity measures analyzing a heterogenous text corpus

Abstract

The article compares the performance of two term specificity measures, Cohen’s d and Z-score, when analyzing political and media discourses on Russia’s war in Ukraine in four languages and five countries. In addition to linguistic and stylistic heterogeneity, 3,347 texts included in the corpus have variable length. The two measures display convergent validity, as confirmed by various performance metrics. It is argued that the measures can be adapted to a broader range of tasks in information retrieval and digital humanities, in addition to their usefulness for text mining and content analysis.