Predicting Poets' Origins from Verse: A Computational Analysis of Regional Linguistic Fingerprints in the Complete Tang Poems

The study presents a computational analysis of Tang-dynasty poetry to predict the geographic origins of poets based on linguistic features. By constructing a corpus of 357 poets and employing character n-gram TF-IDF alongside interpretable features, the authors achieved a classification accuracy of 69% for broad regional origins, surpassing the majority baseline of 53%. The findings highlight the influence of geographic and temporal factors on poetic language, revealing a distance-decay effect and historical shifts in regional styles, while demonstrating that traditional methods like TF-IDF can effectively capture these linguistic signals, suggesting implications for the use of machine learning in literary analysis.