Based on these visualizations I don’t think that the reasoning behind individual contributor choices is readily apparent. The information I am able to parse is centered around the strength of connections, but not the meaning behind them. I think any meaning I could try to derive based solely on this visualization would have a lot of bias and assumptions. In the code.org video from this week regarding search engines, companies such as google use demographic and location algorithms to return what is assumed to be the most relevant results. The political implications of how that algorithmic code fosters a feedback loop where users are only seeing results in line with their pre-existing ideas and bias has been widely felt. Unlike the initial dream of the web to use hyperlinks and scan multiple connected sources of data to further human knowledge, search result algorithms may inhibit people from developing new ideas or collaborating across political and cultural domains. Similarly, the strength of the connections here doesn’t provide me with deep and nuanced information and tilts my community towards others that make the same choices even though I don’t know their intention or meaning.  It would be interesting if the quiz included secondary questions around decision making. For example, did you choose this song a) personal preference b) for diversity representation c) other. It would offer insight into the political relevance of nodes within the network based on  intentionality not just popularity. 

The most relevant nodes concentrate towards the center of the visualization. These nodes have the most in common with other nodes within the network because they have the highest number of links. We can visually see a high density of crossing edges in the center clusters of nodes. I did think it was interesting that the links in this network visualization don’t explicitly indicate directionality. Knowing the source data, I can assume that nodes that appear as contributor names are directional to songs and not vice versa. It is interesting to chart a walk between contributor nodes through song nodes, particularly outside of contributor communities (Systems Innovation, 2015). Whereas in my contributor community there is only one node of separation between members, within the larger class visualization I have multiple nodes of separation and innumerable potential walks within the network. I did try turning off links and switching on node size- honestly I found it a bit depressing. Rather than seeing the information as highly networked it quickly became obvious that many songs (and people) are irrelevant to the network (myself included) based on network theory.    

Code.org. (2017, June 13). The Internet: How Search Works (video file). Retrieved from https://youtu.be/LVV_93mBfSU

Systems Innovation. (2015, April 18). Graph Theory Overview (video file). Retrieved from https://youtu.be/82zlRaRUsaY

Systems Innovation. (2015, April 19). Network Connections (video file). Retrieved from https://youtu.be/2iViaEAytxw