Do the words journalists choose reveal unconscious political biases or create/reinforce similar biases? The 2016 and 2020 presidential elections made vicious and fierce rhetoric the norm and strong political identification a fact of life. The accusations of “fake news” and bias ring loudly, destroying the perception of a free and fair press and posing a threat to democracy. The challenge for this project is to develop a human-centered process and natural language processing tools to help journalists make less freighted word choices; that is, a detector for partisan language when covering political news.
Through this project, we'll better understand how journalists and news consumers perceive bias via word choice. We'll prototype, build and test potential tools to help journalists find neutral terms for partisan issues.