Unknown

Dataset Information

0

Quantifying the Beauty of Words: A Neurocognitive Poetics Perspective.


ABSTRACT: 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 aesthetic potential 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.

SUBMITTER: Jacobs AM 

PROVIDER: S-EPMC5742167 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

altmetric image

Publications

Quantifying the Beauty of Words: A Neurocognitive Poetics Perspective.

Jacobs Arthur M AM  

Frontiers in human neuroscience 20171219


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 <i>aesthetic potential</i> is proposed. Application of machine learning algorithms fed with this QNA data shows that a classifier of the decision tree family ex  ...[more]

Similar Datasets

| S-EPMC3524573 | biostudies-literature
| S-EPMC7423420 | biostudies-literature
| S-EPMC5771228 | biostudies-literature
| S-EPMC2958742 | biostudies-literature
| S-EPMC2231386 | biostudies-literature
| S-EPMC7805775 | biostudies-literature
| S-EPMC8055116 | biostudies-literature
| S-EPMC6981181 | biostudies-literature
| S-EPMC5842750 | biostudies-literature
| S-EPMC6634368 | biostudies-literature