Yesterday, U.S. President Trump pulled out of a "highly-anticipated" summit meeting with North Korea's Kim-Jung Un. Given the freshness of this story, it'll take some time collect enough articles to do an anlaysis of this specific incident. But, in the meantime, some interesting results from my analysis of Korean-U.S. relations in American news below.
(Data cleaned and analyzed using R tidytext, quanteda, and OpenNLP. Graphs produced by ggplot2 or MediaCloud.)
As we can see above, the majority of the coverage appeared to be between May 7 (when North Korea claimed to have demolished a nuclear test site) and May 21. Using those two weeks as my window, I pulled all articles referencing "Trump" and "North Korea" from four news outlets: CNN (n =96), Fox (n = 114), the New York Times (n = 89) and the Washington Post (208), a total of 507 news stories.
I tagged all the words in the news stories for their part of speech using OpenNLP. I then pulled out all the adjectives, removed duplicates, and screened them for accuracy (OpenNLP has an above 90% accuracy, but the human eye is critical to ensuring quality results). I finally looked at the use of these adjectives in relation to specific actors/parties (mainly North Korea, South Korea, and the United States). Given the effect of political personalization, I consider both the country name and the name of the leader (e.g., "North Korea" OR "Moon Jae-In" OR "President Moon" OR "Moon Jae In") as keywords. I retained the adjective if it appeared within three words of the NK, SK, or US keywords.
Raw counts are presented below (keep in mind the corpus is not perfectly balanced... also, sorry I was too lazy to reorder the charts XD Just so tired and wanted to practice some code):