This Python code scrapes Google search results then applies sentiment analysis (using TextBlob and VADER in tandem), generates text summaries (4 different methods) for each classification, and ranks stopwords-scrubbed keywords per classification.
Results are displayed on-screen and are also saved as text files.
By changing 2 URLs, the search engine homepage and the search engine results page, this code should work with Bing or any other search engine.
Click here to read the WordPress blog article about this project.