This is our final project for this class. Ours is called Fantastic Disney Fanatics. Basically, what we hoped to do with the project was analyze how Disney female characters have changed throughout films over time through reviews from the audience. We cherry picked several movies, including Snow White and the Seven Dwarves (1937), Cinderella (1950), Sleeping Beauty (1959), The Little Mermaid (1989), Mulan (1998), and Frozen (2013). Afterwards, we analyzed the reviews using Antconc and Voyant. A timeline was created to augment the conclusion. There was a lot of hair-pulling and stress to make the end project turn out the way it did, but I feel as though it is a success. In any case, I hope you all enjoy visiting the site. Leave comments if you wish~
The Team- Brandon Raidoo & Jamie Martinez
The Project- Brubeck’s Jazz Tour
The Project that Jamie and I undertook was to exam the travels of Dave Brubeck on his famous 1958 Jazz tour. We endeavoured to answer some research questions. Through a combined effort of sorting through the Holt-Atherton Special Collections at the University of the Pacific we were able to look at all the information. One of our biggest questions was how was Brubeck perceived where he went. Through the use voyant we were able to look at the key words used to describe Brubeck and his Band. The second major questions was where was he travelling in the countries he visited along with what countries did he visit. To answer this question we created a google map through google fusion tables after painstakingly entering about 100 data points to be analysed. To find out what were the key words were that described Brubeck, to read some wonderful transcriptions of what was written about him, or to take the journey that Brubeck did on his jazz tour go on ahead to the site cited above.
There isn’t a link on canvas yet so I am putting this here
These past couple weeks we have been working with an application called Palladio. To be honest I don’t really like it and its been very hard for me to navigate and has given me troubles; however, I did find it helpful how Professor Schroeder gave us the walk through sheet for how to use Palladio to creating graphs and maps and without that I’d probably have no idea of how to do it. I didn’t get far enough to create a map because I got stuck at the inserting the data stage. I was able to insert the first attribute data set but when I tried to put the second one in to create the map, Palladio wouldn’t let me for some reason, which was very frustrating. I was following all the steps and it still wouldn’t work.
Network Analysis… What does that mean to you? According to the internet, network analysis is defnied as, “the mathematical analysis of complex working procedures in terms of a network of related activities.” Now, this may seem like a daunting definition, but to put it in simpler words, its the connection between “types” of data.
Previously, we worked with a website named “Palladio,” which allowed us to take the data from the Cushman collection (photos) and place them throughout a map that we created, based on where the photos were actually taken. This was one of the basic functions of Palladio. As I worked with the website more, I began to understand more and more of the things you could do with it; not just maps.
Maps, however, were pretty intriguing. I was able to figure out how to place pictures on the map, and even make points BIGGER, dependent upon how many pictures were taken in that area.
Now, I wasn’t able to be in class on Thursday due to an incident that occurred, but I tried to keep up with the readings, and in-class work. I went through and read all the blogs about network analysis, and since I wasn’t able to do the in-class work with it, I am using the visualizations that “
” had posted.
This first image appears to be un-linked, and by that, I mean that the points are plotted on the map, but aren’t connected or interacting with one another. Basically showing that the points have no relation to one another.
For this second mapping, I can see the relations and interactions between the points, and what is being represented. I can also see that Neuman(s) is receiving help from others.
Google Fusion Tables
Palladio is an interesting tool to use and is a bit more complicated than advertised. While other mapping programs were guessable in that the steps used to generate a map could be done by clicking buttons randomly (please take this with a grain of salt – I’m joking for the most part), Palladio would almost certainly require a guide. Additionally, there are glitches in the program when occasionally, the program would freeze. In the tutorial, I tried out both Palladio (the first picture) and Google Fusion Tables (the second picture) for mapping. While Google Fusion Tables also works for a similar result, its functions are nowhere as in depth as Palladio. It is, however, easier to use. As seen in the picture, both have a function that depicts what type of relationship people have to each other. Google Fusion Tables does utilize color and directional arrows, and Palladio does offer a function that allows a person to switch off between two data sets. The advantages of Palladio and Google Fusion Tables are clear. For me, I’d prefer using Google Fusion Tables for the ease of use and when I wanted to make something more visually appealing. However, Palladio would be the main choice if I were to seriously map out relationships for the purpose of studying them.
This time around, I focused mainly on Palladio. The uses of Palladio consist mostly of mapping out relationships between two or more things, represented by nodes and edges, as explained by Scott Weingart in his article, “Demystifying Networks.” It is useful not only for mapping out relationships but also seeing how people connect with each other. As Kieran Healy demonstrates in her article, “Using Metadata to Find Paul Revere,“ she is able to utilize several matrices and mapping tools to not only show who has a relationship with each other but which of their parties connect the most. In the present-day setting, something like this would be extremely useful for ferreting out hostile groups. And even if not for that, it would still prove to be useful in gathering data, allowing a person to more accurately aim their advances towards the right group (i.e. attempting to research a certain topic and going around talking to related individuals.
Palladio with sized nodes to depict the prevalence of person
In the example I used, the data set was of primarily the relationships of Ralph Neumann to others. The relationship network demonstrates who was a giver and who was a recipient of help (if not both) during the time of the Holocaust. Ralph Neumann was hiding underground along with several other people to escape prosecution. Here, as opposed to the first picture of Palladio, I used sized nodes show the people who were connected with each other the most and those who received the most help. As this is a data set on Neumann, naturally, he had the biggest node of all. There was also a timeline function that allowed a person to edit the time of help, which can be seen in the second picture.