{"id":1811,"date":"2019-12-07T02:19:45","date_gmt":"2019-12-07T07:19:45","guid":{"rendered":"https:\/\/mathewkiang.com\/?p=1811"},"modified":"2020-02-04T12:40:32","modified_gmt":"2020-02-04T17:40:32","slug":"collaboration-network-from-2010-to-2019","status":"publish","type":"post","link":"https:\/\/mathewkiangcom.local\/2019\/12\/07\/collaboration-network-from-2010-to-2019\/","title":{"rendered":"Collaboration network from 2010 to 2019"},"content":{"rendered":"<span  class=\"x-dropcap\" >I<\/span> have been trying to wrap my head around working with temporal networks \u2014 not just simple edge activation that changes over time but also evolving node attributes and nodes that may appear and disappear at random. What better way than to work with a small concrete example I&#8217;m already very familiar with?<\/p>\n<p><!--more-->Here is an update to a post I made, a little over a year ago, about <a href=\"https:\/\/mathewkiang.com\/2018\/06\/17\/my-collaboration-network\/\">my collaboration network<\/a>. Each paper or project (blue) is connected to a collaborator (red). The size of the blue node is the cumulative citations that paper has received since publication to the current year (upper left).<\/p>\n<p><a href=\"https:\/\/mathewkiang.com\/weblog\/wp-content\/uploads\/2019\/12\/network_evo-1.gif\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-1813\" src=\"https:\/\/mathewkiang.com\/weblog\/wp-content\/uploads\/2019\/12\/network_evo-1.gif\" alt=\"\" width=\"2250\" height=\"2250\" \/><\/a><\/p>\n<p>Code available at <a href=\"https:\/\/gist.github.com\/mkiang\/8a815911c95c37574ac883261a992fbf\">this gist<\/a> (note that it&#8217;s two files).<\/p>\n","protected":false},"excerpt":{"rendered":"<p>have been trying to wrap my head around working with temporal networks \u2014 not just simple edge activation that changes over time but also evolving node attributes and nodes that may appear and disappear at random. What better way than to work with a small concrete example I&#8217;m already very familiar with?<\/p>\n","protected":false},"author":1,"featured_media":1899,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[132,113,44],"tags":[],"_links":{"self":[{"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/posts\/1811"}],"collection":[{"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/comments?post=1811"}],"version-history":[{"count":4,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/posts\/1811\/revisions"}],"predecessor-version":[{"id":1898,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/posts\/1811\/revisions\/1898"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/media\/1899"}],"wp:attachment":[{"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/media?parent=1811"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/categories?post=1811"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mathewkiangcom.local\/wp-json\/wp\/v2\/tags?post=1811"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}