Code developed for a final project in Master's level introductory Python class.
Program has two movie datasets in varying structures.
The movies are read in and instances are created for each unique movie.
The movie summaries are analyzed with NLTK to categorize which words are nouns or adjectives. Additional analyses like determining most popular movies, most frequent nouns and adjectives, and movie title length are completed.
Future improvements:
- Use NLTK to perform part of speech counts rather than using a Pandas DataFrame
- Determine if there is a correlation between sentiment of movie summary or title and popularity.