| Summary: | This article examines whether authors change their styles when writing in different genres, like poetry and prose, particularly under the metrical constraints of the former. Using a corpus of works by five modern Egyptian authors, we analyse the effectiveness of N most frequent words and N most frequent morphological segments in distinguishing between poetry and prose written by the same author. Through supervised and unsupervised machine learning techniques, we demonstrate that authors exhibit distinct stylistic fingerprints in each genre, influenced by the unique conventions and constraints of each form. Results show that each author uses two different stylistic prints when writing prose and poetry. However, when mixing poetry and prose together, all genre-related texts cluster separately, potentially causing author obfuscation. Findings also show that the frequent word method is sufficient for accurately attributing authorship when it comes to mixed-genre texts. In short, the tested linguistic standard features prove resilient across different genres and even survive the constraints of formal poetic meter.
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