Computation Analysis for Identifying the Protagonist and Antagonist and their Sentiments in Harry Potter Books

Abstract

The main goal of sentiment analysis is to find the text polarity (positive or negative). Sentiment analysis can be Natural language processing and computational literary studies have long been interested in sentiment analysis, which can be used to infer relationships between fictional characters. This study uses sentence-based semantic analysis to analyze sentiment in the Harry Potter series. The findings showed that among the primary characters with heroic attributes, Harry Potter scored the most positive polarity; Voldemort scored the most negative polarity, and Hermoine scored the neutral polarity.