1951-2000 State of the Union


  1. generations-8.30176 (11 times)
  2. near-8.20490 (9 times)
  3. shape-7.35690 (5 times)



  1. future of (22 times)
  2. future is (11 times)
  3. future generations (7 times)


  1. the future (144 times)
  2. our future (35 times)
  3. for future (14 times)


future generations-10

our future- 35


our future

  1. 1953-Truman
  2. 1959-Eisenhower
  3. 1970-Nixon








First, I want to say that I had a much better and easier time with this lab than the lab before. I really liked working in Antconc (even though it would crash on me sometimes)! I think that part of it was that it was a bit easier and less time consuming but mainly, I think that I had a better time doing this lab because it was more interesting. I really liked seeing all of the different biagrams within the corpus.

The State of the Union addresses are different from normal English language because they are dealing with a certain thing that is not exactly exclusive but almost so, to the speeches. They use the words: congress, America, years, untied, states, free, security and other words like these more than they are used in English language aside from these State of the Unions. These differences between general English language and these State of the Unions speeches tell us a few things. One thing that the differences tell us is that the speeches are just that: different. They talk about specific things. More than that, they talk about unique things and unpopular things. We can also gather from these differences, the subjects of the speeches and some sort of context in which the speeches are about. For example, we know that the idea of “our future” was an important and reoccurring topic in Truman (1953), Eisenhower (1959) and Nixon’s (1970) speeches. We can also see that these speeches are talking about the country, the government, years (past and/or future), freedom, etc., more than in general English language.

Working in Antconc does many things, only which a few of them I know and experienced. However, from my experience working in and experimenting with the software, I learned that Antconc shows the relationships of words in an entire corpus. It can show how many times a word is used or even a phrase. It will also show you the frequency of the word and then point you to the sentence where it is used. This is helpful for researches of literary studies because, well for one, it saves time. Imagine if someone tried to go through every State of the Union from 1951-2000, and look for the phrase, “our future.” First, it would take forever and second, there could be some times the phrase was used and looked over. With the software, Antconc, it is easier, more efficient, faster and more reliable. A quote that could help narrow down what softwares like Antconc do for researchers of literary studies and the benefits is this one from Michaela Mahlberg’s article, “Corpus Linguistics and the Study of Nineteenth-Century Fiction, “A crucial feature of a quantitative approach to language is the observation of repetitions. Such repetitions show relationships between patterns and meanings.” My favorite thing that Antconc does though, is compare corpuses against each other, such as the State of the Unions up against the Brown frequency corpus. It was really cool to see the two and how they compared and what words were different.