This project analyzes the word count and sentiment of H.P. Lovecraft's stories to explore potential correlations between story length and emotional tone.
Presentation: View the presentation
- Word Count Distribution: Analyzes the typical length of Lovecraft's stories and identifies outliers.
- Sentiment Analysis: Examines the emotional tone of the stories, determining whether they lean positive, neutral, or negative.
- Correlation Analysis: Investigates any relationships between the length of a story and its sentiment score.
- Lovecraft's Fictional Works: Scraped all fictional texts by H.P. Lovecraft from hplovecraft.com.
- Word Count: Total number of words in the story.
- Sentiment Score: A value indicating the emotional tone (ranging from negative to positive).
- Word Count Distribution: Visualized using a histogram to display the spread of word counts, with an indication of the average.
- Sentiment Score Distribution: Visualized using Kernel Density Estimation (KDE) to illustrate sentiment across the stories.
- Sentiment vs. Word Count: A scatter plot to explore the potential relationship between story length and sentiment.
- Word Count: Lovecraft's stories vary significantly in length, with some notable outliers.
- Sentiment: Most stories have a neutral to slightly negative sentiment.
- Correlation: There is no significant correlation between story length and sentiment.
- Deep Learning for Sentiment: Implement deep learning models for more accurate sentiment analysis.
- Project Link: This project will serve as a new "remastered" basis for my previous project: Lovecraftian Entity Generator: Unveiling Cosmic Horrors.