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dc.contributor.advisorIves, Maura
dc.creatorKim, Hoyeol
dc.date.accessioned2023-02-07T16:19:50Z
dc.date.available2024-05-01T06:05:47Z
dc.date.created2022-05
dc.date.issued2022-04-19
dc.date.submittedMay 2022
dc.identifier.urihttps://hdl.handle.net/1969.1/197350
dc.description.abstractThis dissertation is article-based, consisting of four chapters with two themes: colorization (chapters 1 & 2) and sentiment analysis (chapters 3 & 4). Chapter 1, “Victorian400: Colorizing Victorian Illustrations,” reveals my methods for creating, curating, and validating the Victorian400 dataset for colorizing Victorian black-and-white illustrations. Victorian400 is a nineteenth century illustration dataset consisting of 400 colorful images that is helpful for testing and developing deep learning models. I tested the Victorian400 dataset with the pix2pix model, which is a conditional generative adversarial network (cGAN) model, to verify the dataset for colorizing black-and-white illustrations from the nineteenth century. Chapter 2, “Case Study: Using Machine-Colored Illustrations of Charles Dickens’s Fiction in the Classroom,” addresses the pedagogical usage of machine-colored illustrations in the English classroom based on my case study. I discovered that students often preferred either no illustrations or machine-colored illustrations to hand colored ones. In chapter 3, “Sentiment Analysis: Limits and Progress of the Syuzhet Package and Its Lexicons,” I explore the limits and progress of the Syuzhet package, a sentiment analysis tool in R, for the sentiment analysis of literary texts. I compare the four sentiment lexicons (Syuzhet, Bing, Afinn, and NRC) used in the package. I also test Syuzhet, SentimentAnalysis, sentimentr, RSentiment, and VADER (Valence Aware Dictionary and sEntiment Reasoner) with seven different sentences to see how each lexicon-based sentiment analysis tool generates sentiment scores. In chapter 4, “Dickensian Sentiment and Sentiment Analysis of Victorian Novels,” I perform sentiment analysis on three Victorian novels using BERT (Bidirectional Encoder Representations from Transformers) in tandem with a dataset I created for the sentiment analysis of Victorian fiction, in order to see if sentimentality is revealed in Charles Dickens’s Our Mutual Friend, George Eliot’s Middlemarch, and Charlotte Brontë’s Jane Eyre, since sentimentalism was a primary social value in Victorian society.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectDigital Humanities
dc.subjectComputational Literary Studies
dc.subjectColorization
dc.subjectSentiment Analysis
dc.subjectVictorian Literature
dc.subjectMultilingual DH
dc.subjectVictorian400
dc.subjectSyuzhet
dc.titleComputational Approaches in the Humanities: from Sentiment Analysis to Deep Learning Colorization
dc.typeThesis
thesis.degree.departmentEnglish
thesis.degree.disciplineEnglish
thesis.degree.grantorTexas A&M University
thesis.degree.nameDoctor of Philosophy
thesis.degree.levelDoctoral
dc.contributor.committeeMemberEarhart, Amy
dc.contributor.committeeMemberRoss, Shawna
dc.contributor.committeeMemberHuang, Ruihong
dc.type.materialtext
dc.date.updated2023-02-07T16:19:51Z
local.embargo.terms2024-05-01
local.etdauthor.orcid0000-0002-2049-7531


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