Help users find information about how views and news on a topic have changed throughout time and locate specific positive and negative articles.
What it is
We developed a webapp that queries the New York Times database for relevant articles throughout a specified time period based on a keyword entered. We analyse the positive / negative tone of the articles with a tool based off of AFINN, a list applying positive and negative values to words. The exceptionally strong results are displayed on a timeline and color coded based on how positive or negative the abstracts, lead paragraph, and headline are.