Going into this assignment, I was quite curious to see how diverse the song selections would be throughout the class. I have a lot of experience studying music, arranging compositions, and performing with various musical ensembles and orchestras, so discussing diverse repertoires is something I adore. One of my main fears whenever examining this kind of data is that one group or musical genre will be overly represented, which has historically oftentimes been the case; however, I was pleasantly surprised to see that many of the most popular options (represented by the larger nodes) were from all over the globe. 

I focused much of my examination on the ‘edges’ in each community. Edges, as explained by Systems Innovation (2015), represent the path walked between two nodes. In this case, edges represent individuals and their connections to one or numerous song choices; it is through the songs located at these connective nodes that a walk can be formed between individuals and their choices. The community with the most edges, which indicates the most overlap in song choices both amongst different classmates and across multiple songs in the same community, took place in Community 1, seen below.

The actual groupings of the tracks themselves are quite interesting to me. While I know theoretically that they have all been grouped based on the similar choices of participants, it still feels strange seeing the tracks which have been grouped together, as the tracks placed in each community are oftentimes wildly different from one another. For example, placing Track 2, 9, 20, and 23 (in the image above) in the same ‘community’ feels inherently incorrect based on the diversity of genre.

However, these ‘bizarre’ groupings make sense in the context of the task, as it supports the idea that the majority of the participants of the quiz tried to choose diversity to better represent the human experience. The task was, after all, to curate a list of 10 songs to capture the beauty of Earth and humanity.  Although we cannot be certain of the exact reasoning behind every individual’s song choice simply by examining this visual, we can clearly identify that people who chose certain songs over others tended to align their other choices with others, rather than having very little overlap. To support this, my own name is present in each of the communities except for Community 3, seen below, as I chose neither of these options; yet, with all the other communities, I tended to choose at least two of the available tracks grouped within that community.

One way this visualisation may fail is in showcasing which pieces were not chosen as frequently. As all we could do within the quiz was to input our choices without any extraneous explanation, there is no way to understand why certain pieces truly resonated with the group over others. Null choices are not as easily examinable with these visualisations due to this, although we can clearly identify which songs were more popular over others through looking at the size and strength of song nodes, which correlate positively with increased student choice.

References

Code.org. (2017, June 13). The Internet: How search works.  [Video]. YouTube.

Systems Innovation. (2015, April 18). Graph theory overview.  [Video]. YouTube.

Systems Innovation. (2015, April 19). Network connections. [Video]. YouTube.