Data Driven Journalism – Mahima Singh is a data journalist at the Palm Beach Post in South Florida – Link to full text of this article: “Donald Trump’s relationship with the media has been a constant tug of war. Even before he became the President of the United States, the collective opinion about him in news kept shifting. While today the sentiment in the mainstream media seems overly negative towards Trump, a year ago it was less polarized. The idea – In 2016, as I read news about the president’s campaign, his election and then his inauguration, I felt that there was a sudden shift in the way news media was talking about Trump, especially during the lead up to his inauguration and the first few weeks of his presidency. I wanted to see if data could prove my hypothesis that there was a shift in news sentiment towards Trump before and after his inauguration. For the final project of our natural language processing class at Syracuse University, Daniela Fernández Espinosa from the Information School, James Troncale from the Linguistics Department and I, built a prototype sentiment analyzer to help political figures make better media strategy plans. I visualized the results of that project and hosted it on my GitHub. Text analysis There have been multiple sentiment analysis done on Trump’s social media posts. While these projects make the news and garner online attention, few analyses have looked at the media itself. During the presidential campaign in 2016, Data Face ran a text analysis on news articles about Trump and Clinton. The results gained a lot of media attention and steered conversations. I planned to follow a similar approach…”