This project features sentiment analysis conducted on the text of the Harry Potter book series by JK Rowling. Exploratory data analysis and data visualizations are created within a Jupyter notebook, including a themed word cloud. The VADER package in Python is utilized to assign sentiment to each sentence of text from each book, allowing for trends to be captured in sentiment over time. Naive bayes classified is then used to provide most notable text features of both positive and negative sentiment.
- Sentiment Analysis
- Naive Bayes Classifier
- Jupyter Notebook
- Python
- R Studio
- NLTK - Python
- Pandas - Python
- WordCloud - Python
- VADER - Python
- harrypotter - R Studio
- Jupyter Notebook - Exploratory Data Analysis
- Jupyter Notebook - Word Cloud
- Jupyter Notebook - Sentiment Analysis
- Images - Used to compose Word Cloud
- Background.jpg
- Footsteps.png
- HP_WordCloud.png
- Maurader_Logo.png
- Mauraders_Map.png
- Thunderbolt.jpg
- Font - Used to style World Cloud
- Lumos.tff
- Book Text - Output of Harry Potter text from R Studio
- HPBook1.txt
- HPBook2.txt
- HPBook3.txt
- HPBook4.txt
- HPBook5.txt
- HPBook6.txt
- HPBook7.txt
- Output - Files created in Notebooks
- Exploratory Data Analysis
- df.xlsx
- HPavgwords.png
- HPtotalwords.png
- HPlongchaps.png
- HPshortchaps.png
- Word Cloud
- HP_WordCloud_FINAL.png
- Sentiment Analysis
- HPTimeplot.png
- Exploratory Data Analysis