State of the Union: The words, the facts, the data

Published on February 5th 2019

Here’s the data behind President Trump’s 2019 State of the Union address.

We analyzed the words in his latest address to Congress, alongside every such speech since 1980. From immigration to war, here’s an analysis of each president’s words.

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Methodology

The State of the Union is a Constitutionally-required address from the president to both branches of Congress. It serves to update the country on the current conditions of our democracy. Technically, a president’s first address to Congress is not a State of the Union, but it serves the same purpose and merits inclusion.

To create the analysis, we used transcripts from the American Presidency Project and used R to compile the text and count word frequency. Common words (“and”, “the”, etc.) and words that occur frequently in the entire corpus (“states”) are largely filtered out. The 2018 word count is based upon the speech transcript distributed prior to delivery.

More information, including sources, is available by clicking on the legend, which will navigate to each individual metric page.

The following metrics have been adjusted for inflation: median annual wage, GDP per capita, private fixed investment (non-residential), individual income taxes paid, corporate taxes paid.

<ExpandSection title="R code snippet">\n Pre-condition: SOTU addresses are separately stored in working directory (i.e. 1980.txt)\n \n ```R\n for (year in 1980:2017) {\n \n corpus<-scan(paste(year,".txt",sep = ""),"character",sep="");\n corpus<-tolower(corpus);\n \n

#Split corpus\n
words<-strsplit(corpus," ");\n

\n

#Calculate word counts\n
words <- unlist(words);\n
words.freq<-table(words);\n

\n result <- data.frame(names(words.freq), as.integer(words.freq));\n write.table(result, file = paste(year,".csv",sep = ""), row.names=FALSE, col.names=FALSE, sep = ",");\n \n rm(corpus,words,result);\n \n }\n ```\n \n Post-condition: Words and counts are stored as a csv file (i.e. 1980.csv)\n </ExpandSection>

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