Sentiment Analysis of the Harry Potter Series Using a Lexicon-Based Approach-Reference-Cited by-同舟云学术

Sentiment Analysis of the Harry Potter Series Using a Lexicon-Based Approach

Published:2022-02-18 Issue: Volume: Page:263-291
ISSN:2328-2762
Container-title:Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media
language:
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Author:

Al Mamun Md Habib¹,Keikhosrokiani Pantea¹^ORCID,Asl Moussa Pourya²^ORCID,Anuar Nur Ain Nasuha²,Hadi Nurfarah Hadira Abdul²^ORCID,Humida Thasnim³

Affiliation:

1. School of Computer Sciences, Universiti Sains Malaysia, Malaysia

2. School of Humanities, Universiti Sains Malaysia, Malaysia

3. Dept. of Mass Communication and Journalism, Begum Rokeya University, Rangpur, Bangladesh

Abstract

The objective of this chapter is to conduct a sentiment analysis of the Harry Potter novel series written by British author J.K. Rowling. The text of the series is collected from GitHub as an R package provided by Bradley Boehmke. The chapter analyzed the text by R programming to explore dominant sentiments using a lexicon approach of natural language processing (NLP). The results revealed that Professor Slughorn scored the most positive sentiment among the main characters that have heroic qualities; Death Eaters had the most negative sentiment among the anti-hero characters; negative sentiment in the text around the anti-hero characters increased significantly, while the positive sentiment around the hero characters remained constant as the story progressed throughout the series; among the series of novels, The Deathly Hallows contained the most negative sentiment; among all the houses of Hogwarts School of Witchcraft and Wizardry, Hufflepuff had the most positive sentiment; and each book of the series appeared negative until the final chapter, which always ended with a positive sentiment.

Publisher

IGI Global

Reference35 articles.

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