Task 9: Networking the Golden Record

Creating Networks (based on selections for communicating with intergalactic life)

Full disclosure: I did not complete the quiz. I was in such a rush to post my web link for Task 8 that I completely forgot what was on the "next" page of the module. THEN, for some reason, Canvas stopped emailing me sometime after Task 6, so I didn't get any of the announcement emails from Ernesto. This happened to me last term as well. I updated my email address to my "gmail" one on Canvas, as my friend uses her gmail account and has never had an issue with receiving emails.

End preamble.

For Task 9, I had to analyze the groupings from a third party perspective, so I chose to put myself in a few of my classmates shoes, including checking their blogs to see what their thoughts were on their "groupings".

In the first image, the first thing I noticed was that there were only two people in the "networks" of dark green and orange. This intrigued me immediately. What did Evan and Ben have in common (or not in common with the rest) that put them in their own separate community? Same with Jennifer and Charles.

Upon examination, it looks like Evan and Ben chose 5/10 of the same songs. Many of their commonalities were songs from other countries , which makes me wonder if they were drawn towards cultural music, or perhaps liked that those songs were more unique than some of the western ones. Jennifer and Charles had remarkably similar lists! With only ONE song being different, they chose 9/10 of the same songs - wow!

This piqued my interest. The way I see the first graphic is that Evan and Ben should have just as much in common as Jennifer and Charles, however that simply isn't the case. Jennifer and Charles were one song away from having the perfect match, indicating that they must be very "like-minded", while Evan and Ben were only batting 50% on their list of commonalities. Charles indicates that he tried to leave his western bias out of his decisions, resulting in his cultural selections from around the world. Jennifer also made a comment about trying to remove her personal bias from her selections. Reading these blogs brings me to a new question - does removing your personal bias provide valid data when trying to determine how "alike" members of a community are? Although most participants had reasons for their choices, were their choices reflective of who they are as a person? Is it fair to claim that two people are "like-minded" based on song selections as there can be so many variables influencing their decisions? For instance, I know that my own musical preferences change depending on my mood, the time of day, other people around me, and my current activity. I think a more valid method of data collection to determine like-mindedness would be if the activity was open, and participants got to choose their OWN 10 songs which they deem important enough to send out into the galaxy, as opposed to having a narrow selection of 27, most of which have never been heard.

The second image of data shows the names of participants in the same location as the first, with their "community colour", but also shows a web of connections. I assume that these connections are similar song choices. I find this image hard to decipher, as it appears to me that everyone is connected one way or another. I suppose that's a fair assumption as most people probably have at least 1 song in common with each participant.

The third image shows the song titles, and their connections with the participants. This is where we can analyze which song was the most and least popular with our cohort. This data can also be skewed as it appears that not all members of our cohort are represented... There are 20 members of our cohort, and only 17 dots represented here. I know that I am for sure missing, but it appears that there are also two others. This is 30 song selections which have not been accounted for. Having just finished teaching the importance of voting to my class in our 2019 Student Vote for the Federal Election, I feel that I have let my cohort down a bit as the data is not an accurate representation of our group. There are many factors at play for the selection of music, it appears that most members of our community used a specific set of criteria to select their 10 songs. Besides personal bias, participants of different generations or cultural backgrounds may choose using a different lens. Participants who are familiar with classical music may have been influenced by the options to choose Mozart or Bach. Some participants may not have much of a musical appreciation at all, and randomly selected their songs.

At the end of the day, the networks created by these images are "graph theories", a mathematical concept. The data is strictly quantitive, and doesn't take any qualitative data into account. To me, comparing "like-mindedness" is a very qualitative concept, much more complex than the algorithm of nodes and edges in a network, and choosing 10 songs from a playlist of songs we've never heard.