SAHIL ALI - PORTFOLIO

Inspired by childhood memories of Harry Potter, this project uses Python to scrape text about Severus Snape and analyze his emotional landscape through sentiment analysis. By combining web scraping with natural language processing, I decoded the complex feelings and recurring themes in Snape's story.

Project Objective

To extract and analyze textual data about Severus Snape to understand his emotional nuances and identify key words that define his character.

Web Scraping Process

Using Python libraries like BeautifulSoup, I extracted relevant paragraphs from dedicated fan sites and wikis. The raw text was then cleaned and structured into CSV files for analysis.

Sentiment Analysis Methodology

Leveraging NLTK's SentimentIntensityAnalyzer, I classified Snape's sentiments into categories such as worry, contempt, anger, and protectiveness. This revealed the emotional texture of his narrative.

Key Findings

• Worry (22.51%) dominates, reflecting Snape’s constant concern throughout the saga.
• Contempt (19.32%) and Anger (14.94%) highlight moments of disdain and frustration.
• Protectiveness (10.06%) shows Snape’s hidden guardian role.
• Sarcasm, sacrifice, ambiguity, and affection also color his emotional profile.

Top Keywords

• Snape appears 703 times, central to the narrative.
• Harry, Dumbledore, Voldemort underscore key relationships.
• Lily symbolizes poignant emotional ties.

Visual Insights

Conclusion

This project uncovers the layered emotions of Severus Snape through data science techniques, blending storytelling with analytics to reveal the complexity behind one of literature’s most enigmatic characters.