This project uses text mining techniques on the Harry Potter film scripts to analyze patterns, trends, and emotional dynamics. The analysis aims to provide insights into plot evolution, character development, and the series' emotional trajectory.
The analysis is based on a dataset compiled from GitHub, including scripts from all eight Harry Potter films.
The approach includes data wrangling, exploring initial hypotheses about character impact and word usage, text analysis through TF-IDF and sentiment analysis, and visual representation of our findings.
- Character Importance: Identification of central characters based on dialogue, revealing insights into character prominence and narrative focus.
- Word Usage and Spells: Analysis of specific spells and words highlights thematic focuses across the films.
- Sentiment Analysis: Examination of emotional sentiment in dialogues uncovers mood and tone shifts within and across the movies.
- Thematic Patterns: Exploration of themes and motifs reveals emphasis on certain subjects in different saga parts.
The text mining exploration of the Harry Potter films uncovers narrative structure, character dynamics, and emotional depth, offering a new understanding of this magical universe.