Networking in Maps, and a little confusion.

Previously, I made a blog post about Palladio and creating “special” maps. This week in class, we went a little further and used Palladio to make a map of networks. In the article “Demystifying Networks”, Scott Weingart explains network in the simple terms of “stuff” and their relations.

We were given a data set to use by Marten Durer h people in the time of World War II that showed such things as t heir gender, who gave/received help, and who may have given help or received it. It was a lot of information to take in since it was all on a spreadsheet, but once I put it into Palladio and generated a network map, there were different options that I could choose so I could see the information in different ways.

giver and reciever new

The first attempt of the networking maps that I made is of the one above. I screenshotted this from the Palladio website and whenever I do that it does come out blurry so the names are probably hard to read on this. For this map, I selected it to show the network between the gives and receivers.  Essentially, this map shows who gave help to who and who received it and the string of networks that these people were in. It’s hard to see, but there are darker circles in this map that represent people who both gave help and received it as well.


The second map I attempted to do was “race”. This map essentially made separate networks of people based on their race and it was actually kind of interesting. Part of the map cut off in the screenshot, but there were more networks down below that were very minimal. The biggest network in the middle was all German names and had multiple repeats. The people with the same last name were networked together. Below the large network were two smaller network of people also grouped together by their race. What I found interesting was that “AushweisNazi” was on the edge of the large network alone connected down to a smaller network. I am not quite sure what that means and couldn’t really figure it out.

I think I had a harder time deciphering what these maps. With the Spacial Maps, everything is clearly labeled and obvious to explain. With networks, there are so many names that are connected that for me, it is hard to tell what they represent. Overall, it is interesting to see how many data points connect though.


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