For part one of the lab, I uploaded the phrase “your eyes” into Bookworm and the google Ngram Viewer. I choose this phrase because I feel like it is romantic and the idea of someone’s eyes is a very common thing throughout literature so I was interested to see how often it has been used. In Bookworm, the highest number got to about 5.7 million in 1920 while the lowest number got to about 4.7 million times in 1880 that it was used in a given year. So there was not a lot of changes throughout time in regards to that phrase.
When I put the phrase, “your eyes” into the google Ngram Viewer, I got about the same graph as I had in Bookworm. Some of the differences though, were that this google Ngram Viewer measured the use of the phrase by percentages and not by actual times used. The other difference was that this graph covered a bigger time frame than that Bookworm. This one went all the way to 2000. The highest percentage being .000544… in 2000 and the lowest .000268… in 1966.
What we can see from these graphs is that the phrase “your eyes has been used pretty much the same amount throughout time and only in the past few decades has grown. It seems to me, after looking at these graphs, that if they kept going, the use of the phrase, “your eyes” would continue to increase.
For the next part of the lab, I uploaded the state of the union topic counts into the multicloud tab of Lexos and created the topic graphs from there. These graphs show us what words are used the most and their importance.
As you can see in these graphs the words states, united, congress, government, public, people, etc. ate in a bigger and different color font so we can gather from that the significance and frequency of them. These words in a state of union address are not all that surprising but some words like favor and hands were surprising for me to see in the graphs. These graphs help get a taste of what the state of the union addresses were like even though we may have not read them. They are important because they show the main topic of the speeches.
For the next part of the lab, I went to the Data Behind my Ideal Bookshelf. Wow! I loved this so much. It took me a second of reading and playing around with the graph to really get what was going on but I thought it was so cool to see how all of the people connected with each other by the literature that they like and own. I loved seeing how many people shared their love of David Foster Wallace’s Infinite Jest or Flannery O’Conner’s Complete Collection of Short Stories. I also thought it was really cool how the bubbles represented people and when you put your cursor on one it would connect to other bubbles that shared some of the same literature with them.
(I tried logging in to fusion with four different accounts and it wouldn’t let me.)