AUTHOR=Jacobs Arthur M. 

TITLE=Quantifying the Beauty of Words: A Neurocognitive Poetics Perspective

JOURNAL=Frontiers in Human Neuroscience

VOLUME=11

YEAR=2017

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2017.00622

DOI=10.3389/fnhum.2017.00622

ISSN=1662-5161

ABSTRACT=<p>In this paper I would like to pave the ground for future studies in Computational Stylistics and (Neuro-)Cognitive Poetics by describing procedures for predicting the subjective beauty of words. A set of eight tentative word features is computed via Quantitative Narrative Analysis (QNA) and a novel metric for quantifying word beauty, the <italic>aesthetic potential</italic> is proposed. Application of machine learning algorithms fed with this QNA data shows that a classifier of the decision tree family excellently learns to split words into beautiful vs. ugly ones. The results shed light on surface and semantic features theoretically relevant for affective-aesthetic processes in literary reading and generate quantitative predictions for neuroaesthetic studies of verbal materials.</p>