{"id":68,"date":"2021-11-07T18:38:50","date_gmt":"2021-11-08T01:38:50","guid":{"rendered":"https:\/\/blogs.ubc.ca\/naishetec540\/?p=68"},"modified":"2021-11-11T11:49:13","modified_gmt":"2021-11-11T18:49:13","slug":"task-9-network-assignment","status":"publish","type":"post","link":"https:\/\/blogs.ubc.ca\/naishetec540\/2021\/11\/07\/task-9-network-assignment\/","title":{"rendered":"Task 9: Network Assignment"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">I will admit that when I loaded the data it was overwhelming at first. The web\/graph of data is an interesting way to represent all the connections that exist within the data. This network represents an extensive amount of information from our previous task.\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-69 aligncenter\" src=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/12132-300x161.jpg\" alt=\"\" width=\"484\" height=\"260\" srcset=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/12132-300x161.jpg 300w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/12132-1024x551.jpg 1024w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/12132-768x413.jpg 768w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/12132-767x412.jpg 767w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/12132.jpg 1049w\" sizes=\"auto, (max-width: 484px) 100vw, 484px\" \/><\/p>\n<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">In looking at the data table of curators there were 21 individuals, who chose 10 songs from a possible 27 pieces. Now forgetting my probability calculations from the finite mathematics course I took during my undergraduate, I can\u2019t tell you <\/span><i><span style=\"font-weight: 400;\">exactly<\/span><\/i><span style=\"font-weight: 400;\"> but I know that would lead to a <\/span><b>very<\/b><span style=\"font-weight: 400;\"> small probability that someone would choose the exact same combination of songs. However, using the formula for combinations (where the order does not matter) we can deduce that there are 8 436 285 possible combinations.<\/span><\/p>\n<p style=\"text-align: center;\"><span style=\"font-weight: 400;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-71\" src=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/combo-300x97.jpg\" alt=\"\" width=\"300\" height=\"97\" srcset=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/combo-300x97.jpg 300w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/combo.jpg 636w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/span><\/p>\n<p style=\"text-align: center;\"><span style=\"font-weight: 400;\">Where n = 27 songs\/ r = 10 chosen songs<\/span><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-72 aligncenter\" style=\"font-style: inherit; font-weight: inherit;\" src=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/combo2.jpg\" alt=\"\" width=\"203\" height=\"228\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Each person has at least a few different commonalities with our peers. It makes for a good metaphor that you can find some sort of connection with anyone. In analyzing the data further, I played around with the different communities first as that was the default facet dimension. <\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-70 aligncenter\" src=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/web-300x159.jpg\" alt=\"\" width=\"377\" height=\"200\" srcset=\"https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/web-300x159.jpg 300w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/web-768x408.jpg 768w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/web-767x407.jpg 767w, https:\/\/blogs.ubc.ca\/naishetec540\/files\/2021\/11\/web.jpg 1021w\" sizes=\"auto, (max-width: 377px) 100vw, 377px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">The community I was a part of was the second one and consisted of four other people and myself &#8211; Anna-Marie MacPherson, Vera Xiong, Justine Johal, and Maurice Broschart. Maurice was the only one who shared every choice with one of us while the rest of us had 1-3 unique choices that no one in our community shared with us. <\/span><span style=\"font-weight: 400;\">Dark was the night<\/span><span style=\"font-weight: 400;\"> was the only song that all 5 of us had chosen &#8211; represented by the larger node in the middle. With only their names as the main source of information, I can make the assumption that we are mostly females in our community and that our names come from different heritages. I am unable to assume age, or where they may live, or any emotional connections to the music they may have based on their personal experiences. This leads me to the part of the picture that is lacking &#8211; the reasoning behind our choices. In our own blogs for Task 8, we described the \u2018why\u2019 or our approach to choosing our 10 songs but looking at the data we can\u2019t make those assumptions on others&#8217; choices. There are many contributing factors to someone\u2019s choices &#8211; gender, age, culture, religion, where they live as well as something as simple as their taste in music.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">From the collective data, the largest node or most chosen was Beethovens 5th symphony and the lowest chosen were Men\u2019s House song and Kinds of Flowers &#8211; both options I did not choose. The graph shows connections between people based on their commonalities, but how would the visualization differ based on our differences?<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>I will admit that when I loaded the data it was overwhelming at first. The web\/graph of data is an interesting way to represent all the connections that exist within the data. This network represents an extensive amount of information from our previous task.\u00a0 In looking at the data table of curators there were 21&hellip;<\/p>\n","protected":false},"author":24937,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,4,1],"tags":[],"class_list":["post-68","post","type-post","status-publish","format-standard","hentry","category-etec-540","category-tasks","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/posts\/68","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/users\/24937"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/comments?post=68"}],"version-history":[{"count":1,"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/posts\/68\/revisions"}],"predecessor-version":[{"id":73,"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/posts\/68\/revisions\/73"}],"wp:attachment":[{"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/media?parent=68"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/categories?post=68"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.ubc.ca\/naishetec540\/wp-json\/wp\/v2\/tags?post=68"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}