{"id":163,"date":"2021-12-07T23:28:03","date_gmt":"2021-12-08T06:28:03","guid":{"rendered":"https:\/\/blogs.ubc.ca\/ncheung540\/?p=163"},"modified":"2021-12-08T00:08:27","modified_gmt":"2021-12-08T07:08:27","slug":"linking-assignment-5","status":"publish","type":"post","link":"https:\/\/blogs.ubc.ca\/ncheung540\/2021\/12\/07\/linking-assignment-5\/","title":{"rendered":"Linking Assignment #5"},"content":{"rendered":"

Task 9: Golden Record Analysis of Networks<\/a><\/strong><\/p>\n

By: Delian<\/strong><\/p>\n

<\/p>\n

My comment + reflection:<\/p>\n

Hello Delian! First of all, I really appreciate the thoroughness and depth of your observations on our community! Thank you for sharing your insight on all the little details of the visualization and taking us through the step-by-step process of your analysis. I also read more into what the other members in our community wrote for their Task 8, hoping that I could gain more insight on why we were grouped together, and I cannot agree more with your observations. <\/span>\u00a0<\/span><\/p>\n

The possibilities for criteria selection were endless and subjective, so I was impressed that the visualization captured us all! And on a side note, I was also confused when I first noticed that the visualization did not contain my name or some our classmates\u2019. I was worried that I somehow did not make it because my selection was too out of range! Later I found out from Prof Pe\u00f1a that the link given to us was indeed for a different section. <\/span>\u00a0<\/span><\/p>\n

I really appreciate that you took the time to read through our group members\u2019 and classmates\u2019 criteria in the previous task, which helped generate your insightful comparisons and conclusions. As you mentioned, the visualization reflected the quantitative data only, and nothing else beyond our names and song choices. I thought that there must have been some distinction that we have in common (other than similarity of the results), for us to be brought together. While I observed that our values did not seem to fully align, you also made an excellent point that \u201cabsence of evidence isn\u2019t evidence of absence.\u201d I cannot agree more, and your point makes me rethink my own conclusion. It\u2019s always a challenge to avoid assumption when working with data, and it\u2019s easy to become just a number.<\/span>\u00a0<\/span><\/p>\n

I like your statement about the predictability factor of the web. We just can\u2019t avoid the content! Whether we clicked on something out of curiosity or accidentally, that decision is already being channelled into our individual web patterns and generated into our results. I remember it would take so long to finally stop seeing something I did not want to see on my feed, just because a friend sent me a link to it once. Nowadays, I\u2019m more mindful with what I click. Circling back to your previous points, it does seem like web algorithms are showing us already predicted content based on its mere assumptions of us (as quantified data), without learning about why.\u00a0 <\/span>\u00a0<\/span><\/p>\n

Thank you again Delian, for your fantastic insight and perspective! It\u00a0definitely made\u00a0me think more about how the web works.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

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