DeepAI AI Chat
Log In Sign Up

A Computational Approach to Walt Whitman's Stylistic Changes in Leaves of Grass

by   Jieyan Zhu, et al.
Columbia University

This study analyzes Walt Whitman's stylistic changes in his phenomenal work Leaves of Grass from a computational perspective and relates findings to standard literary criticism on Whitman. The corpus consists of all 7 editions of Leaves of Grass, ranging from the earliest 1855 edition to the 1891-92 "deathbed" edition. Starting from counting word frequencies, the simplest stylometry technique, we find consistent shifts in word choice. Macro-etymological analysis reveals Whitman's increasing preference for words of specific origins, which is correlated to the increasing lexical complexity in Leaves of Grass. Principal component analysis, an unsupervised learning algorithm, reduces the dimensionality of tf-idf vectors to 2 dimensions, providing a straightforward view of stylistic changes. Finally, sentiment analysis shows the evolution of Whitman's emotional state throughout his writing career.


page 1

page 2

page 3

page 4


Principal Components of the Meaning

In this paper we argue that (lexical) meaning in science can be represen...

Principal Word Vectors

We generalize principal component analysis for embedding words into a ve...

Examining Structure of Word Embeddings with PCA

In this paper we compare structure of Czech word embeddings for English-...

BCSAT : A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations

The presented work aims at generating a systematically annotated corpus ...

The concept "altruism" for sociological research: from conceptualization to operationalization

This article addresses the question of the relevant conceptualization of...