I chose to analyze the phrase “Civil War” in the Bookworm graphing tool. I noticed a big peak between 1860 and 1870. I believe this spike is obvious because the Civil War occurred during 1861-1865. There was also another large spike in 1900. I believe this because the UK experienced the War of the Golden Stool at this time, but the odd thing is the blue line represent the US, whereas, the orange line represents the UK. I think the blue line might experience more peaks because maybe novels were better circulated around in the US than they were in the UK.
This graph was made with Google’s ngrams. I analyzed the phrase “Civil War” again. This graph is of the US. I found the same thing in this graph as I did in the Bookworm’s graph. There is a peak between 1860 and 1880, which is because of the actual Civil War occurring. However, I found something different in this graph that was not as obvious in the Bookworm’s graph. I noticed that there is a dip in the graph at 1920. I believe this may due to the roaring 20’s. The US’s economy was thriving and people just wanted to move on from talking about the war.
Finally, I analyzed the phrase “Civil War” in the UK. I noticed that this graph only recognized a significant peak in the year 1940, whereas, the Bookworm’s graph highlighted a peak in 1900. I believe this graph noticed the impact of War World 2 than the Bookworm’s graph.
In addition, I believe that humanists can utilize these tools because they allow us to notice trends over time that would take us months to discover on our own. They re-imagine time series graphs humanistic principles by making research on qualitative aspects, quantitative through a graph that depicts trends over a period of time. You use this graph to research a word or phrase and a trends over time are given to you, and you can do further research on those peaks and dips in the time-series based off of the quantitative (the years given) information given.
This is a visualization of the most frequent words used in the State of the Union Address. I noticed that the largest words in the word cloud are states, united, and congress. These words did not strike me as odd, but I did notice some odd words listed in the cloud. I noticed works like Mexico, case, and July. These words struck me as odd because I do not know how they were referenced in the various State of the Union Addresses. I believe world clouds are “humanistic” graphical displays according to how Drucker and Klein use the term. They are “humanistic” because they are qualitative. The word cloud mashes up frequently used words from a text and highlights on the words that were most frequent used throughout a specific text. It is also humanistic because it shows this through literary visualization, a word cloud, and not a qualitative visualization, like a regular graph. We can re-imagine this form of graphical display to foreground humanistic, interpretive principles because it reconstructs information into a new and easier display for literary scholars to understand.
In my opinion, the visualization on fredbenenson.com is not clear. I never could understand those graphs because there is too much going on. Therefore, I do not think it is intuitive. I do not think it is clear for what it is being used for. Interacting with the graph gives me less information than the other representations of data further down on the same page. The graph does answer any of my questions to begin with, therefore, I still have initial questions that were never answered. I believe focusing on one specific topic is a way humanists can utilize time series graphs as Drucker and Klein argue for.
This is a visualization of the countries in which artists were born. This visualization can help research data easily by using a visualize pie graph. We could use Google Fusions in our class project to help us compare different aspects of the project and help us make sense of it through visualizations. For example, we could use these to compare different author’s texts from different decades or even different countries. I believe there is a way to use Google Fusions to foreground humanistic, interpretive principles as Drucker and Klein argue for. Google Fusions’ graph are very visual and have a humanistic aspect to them because they turn data into qualitative data by giving us information like countries of birth and qualitative information of that nature.