After watching “A Journey to the Bottom of the Internet,” I participated in a “close your eyes” exercise that prompted me to envision a web of nodes and edges, which I previously referred to as “links.” However, when I applied the information from Module 9 to Palladio, I realized that this web was complex and multi-layered and had a significant impact on our decision-making due to the vast amount of clicks and links involved.
The Palladio tool offers an intriguing way of visualizing data, allowing for customization that can provide more insight and variety into the dataset. However, it’s worth noting that interpreting a dataset without any intention or purpose can lead to a lack of valuable information.
In Assignment #8, we were tasked with curating the “Golden Record,” a collection of 27 songs that represents the world of music. The assignment required us to narrow the selection to only 10 songs based on our criteria. This assignment immediately caught my attention because I knew everyone’s interpretation of the music and the assignment would be unique. For instance, I chose to focus on including alternative perspectives in my choices while amplifying the voices of marginalized groups. In contrast, a colleague might have selected only vocal or instrumental songs or based their choices solely on personal preference. The diverse interpretations of the assignment led to a wide variety of data, highlighting the importance of clear intentions and guidelines when working with data.
My initial focus was on music as I was interested in discovering the most popular songs. To do this, I applied the concept of connectivity from the YouTube tutorial to this context, visualizing how it might apply to the popularity of songs. When looking at the list of curated tracks, I observed that Night Chant was a popular choice with a high degree of connectivity (14 picks). Despite my intuition that this song would be well-liked, it’s worth noting that the degree of connectivity can have negative implications, as the YouTube tutorial illustrates with the example of a virus.
This made me think about how misinformation spreads rapidly through nodes of connected people, becoming popular even if it’s false. The discussion of page rank in “The Internet: How Search Works” emphasizes the importance of relevant results, but it’s important to keep in mind that false theories can still rise to the top if they have a lot of connected nodes. As I contemplated the degree of connectivity in the music context, I couldn’t help but reflect on the larger implications of this phenomenon. Specifically, it brought to mind how misinformation can quickly spread through interconnected nodes, becoming popular even if it is false – False theories and misinformation can go viral if they have enough connected nodes promoting them. This highlights the need for critical thinking and information literacy skills to help individuals evaluate and discern between accurate and false information. Additionally, it emphasizes the importance of fact-checking and verifying sources before sharing information with others, as it can help to prevent the spread of misinformation through interconnected nodes.
Upon examining the image below, I can see a clear connection between the three most popular songs and the individuals who chose them. This suggests that there might be something in common between these individuals, such as similar musical preferences or selection criteria. However, this exercise alone cannot determine what they have in common, as it lacks the necessary information. One question that arises is what this image can tell us about those who selected all three songs versus those who selected only two or one. While this analysis cannot reveal their selection criteria or the reasons behind their choices, it does reveal the presence of a connection between them. This connection could be a starting point for further investigation into the individuals’ shared interests and preferences, providing valuable insights into the music and the curators who chose it. 