Blog Post #7

Due to my classmates’ enthusiasm for the technical activity this week, I decided to go ahead and do it first. Gephi definitely felt intimidating at the start but I think that is do to the large amounts of text and graphs it is synthesizing. And the sheer amount of people and connections in this list is quite staggering! I’ll be honest when I say I felt like my eyes were crossing at certain points. I did find that the tutorial provided helped quell some of my frustration. Afterwords I thought: Well, this kind of program could definitely be useful to scientists! When I looked further at the Gephi site I did notice they mentioned the tool being useful for “Biological Network Analysis” which is “biological data”. They also mention scientific map creation. So, I take that as a yes: Scientists can definitely make a lot of use out of Gephi! I also wonder if Gephi could be utilized when creating maps of fictional characters… (I don’t see why not if the data is inputted. Something to try for fun!)

In terms of the readings, I felt like I understood and engaged with the Weingart reading the most. I would say that the “demystifying” in the title certainly is truthful His writing was clear and easy for me to understand as someone who doesn’t really know much about network analysis. Some of the interjected humor helped as well. I understand nodes better now and their relationship within networks. I knew what a node “was” but not to the degree that I do presently. Now, I’m not sure how well I will remember things like “RDF Triples” as this isn’t my field… But the article is definitely useful for me to keep handy going forward! Maybe this is a silly question but I do wonder: How many nodes would be too many in a network? How much data is too much? Going back to science, I wonder the difficulties that astronomers face when sorting out data they receive after scanning space. I know we’re talking about historical networks but I imagine the datasets are structured similarly… Hm… (Especially since Gephi mentioned science fields. I know there must be more tools to help visualize datasets as well… I’m kind of just thinking outloud now haha!)

Since my field is art history, I also appreciated the article about Queen Mary I’s letters. It was such an interesting way to visualize historical pieces of data while revealing new data. I do wonder how many in my field are aware of programs like this? I say this because there is a joke that Egyptologists can’t use technology! (I’m sure the ones who lean more into the science side of the field would pick things like Gephi up quite quickly.) While I said I would like to play around with fictional character graphs, I’m actually wondering what kind of data I could find in the Armana Letters if I input their data into Gephi since there’s quite a bit of info on them…

3 comments on Blog Post #7

  1. Weingart’s article was definitely a much more approachable read compared to the others from this module. I have a tendency to read articles out of order (based on my personal interest from looking at the title) but reading Weingart first made understanding the rest actually possible. Had I gone out of order, I wouldn’t understand half of what was going on so I think that’s a pretty clear indicator of how well-written his guide was.

  2. I agree that Weingart’s article was the most helpful and easy to follow! I enjoyed that he stated right away who his intended audience was and I think he accomplished explaining network analysis to people with little to no idea what it entailed. Like you, I was also getting lost in some areas and thought these type of tools would be most useful for science or establishing a historical connection.

    My field is also art history and until I read the articles that related directly to it I wasn’t quite understanding the connection. Once I read the art historical articles I finally understood the importance of network analysis and how it could be beneficial for us.

  3. I liked the fact that you looked for a way to incorporate your interest in Egyptology with network analysis. When I first started reading your summary, I had the thought that it seemed good for science but not too usable for art history. Your example changed my mind. I also appreciated the fact that you admitted that you felt you weren’t very technical, but you wanted to try to learn about networks anyway. And your summary made me feel like I would like to tackle the subject myself. Now, I just hope we can see more of your artwork in some of your remaining blogs!

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