{"id":3043,"date":"2015-04-30T17:41:08","date_gmt":"2015-04-30T21:41:08","guid":{"rendered":"http:\/\/research.prattsils.org\/?p=3043"},"modified":"2015-04-30T17:41:08","modified_gmt":"2015-04-30T21:41:08","slug":"networking-the-belgian-beer-landscape","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/visualization\/networking-the-belgian-beer-landscape\/","title":{"rendered":"Networking the Belgian Beer Landscape"},"content":{"rendered":"<p>Belgium is famous for many things: waffles, fries, and chocolate among them.<\/p>\n<p>But beer is probably at the top of the list.\u00a0The Delirium Cafe in Brussels has a beer menu that more resembles a book. It contains over\u00a02,000 different brands and currently holds the Guinness World Record.<\/p>\n<p>In order to get a better sense of the Belgian beer landscape, I looked up the list of every beer:\u00a0http:\/\/en.wikipedia.org\/wiki\/List_of_Belgian_beer<\/p>\n<p>After copying this data into Microsoft Excel, I adjusted it so that I could upload the data into Gephi.<\/p>\n<p>There was a total of 1594 beers.\u00a0The list included four categories &#8211; Beer Brand, Beer Type, Alcohol Content, and Brewery, which I made into nodes.<\/p>\n<p>Then, I created a spreadsheet for the Relationships. The three relationships were Beer Brand &#8220;isa&#8221; Beer Type, Beer Brand &#8220;HasAlcoholPercentage&#8221;, and Brewery &#8220;Brews&#8221; Beer Brand.<\/p>\n<p>I uploaded the node table and relabeled the first two edge table columns to source and target so that I could upload them as well.<\/p>\n<p>Once in Gephi, I received my initial graph of the data. I ran statistical analysis and found the Degree, Network Diameter, and Graph Density. I found that my data was extremely dense, which was going to make it a challenge to visualize. In addition, because this was multinodal data, I was limited in how much I could show.<\/p>\n<p>After understanding my data a little better, I ran Force Atlas 2 to get a better sense of the visual network. The graph remained very dense, so I decided to play with the nodes.<\/p>\n<p><a href=\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2015\/04\/Version3_2-e1430428932293.png\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\" size-medium wp-image-3093 aligncenter\" src=\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2015\/04\/Version3_2-e1430428608816-620x670.png?resize=620%2C670\" alt=\"Version3_2\" width=\"620\" height=\"670\" \/><\/a><\/p>\n<p>I realized that ABV had the least percentage of connections and decided to filter that out. I then re-sized the nodes on my graph and got a great sense of the most popular beer types in Belgium.<\/p>\n<p>I moved on to the preview section and tried to adjust the visualization so that it was more readable. I labeled\u00a0the largest nodes so that it was clear to see the names of the most popular beer types.<\/p>\n<p>However, there was one last step that I wanted to run in hopes of separating the sections. Despite the fact that my data was multinodal, I ran modularity.<\/p>\n<p>After increasing the modularity to 3.0, I discovered four sections, separated by color: red, purple, teal,\u00a0and yellow. I would have liked to edit the colors, but Gephi doesn&#8217;t offer great functionality for this.<\/p>\n<p>Despite this, the colors do offer the viewer a clear sense of the most popular types of Belgian beer\u00a0and which of those types are most related.<\/p>\n<p>The data did make some sense in the end, in that the beer types in the same sections are similar.<\/p>\n<p><a href=\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2015\/04\/Version4-e1430429961290.png\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\" wp-image-3094  aligncenter\" src=\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2015\/04\/Version4-e1430428719944-620x679.png?resize=643%2C705\" alt=\"\" width=\"643\" height=\"705\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<p>Here is a view with larger labels:<\/p>\n<p><a href=\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2015\/04\/Version5-e1430429751448.png\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-3115 size-medium\" src=\"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infoshow\/wp-content\/uploads\/sites\/2\/2015\/04\/Version5-e1430429717864-620x662.png?resize=620%2C662\" alt=\"Version5\" width=\"620\" height=\"662\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>The yellow section was made up of following main beer types: blond, triple, bruin, amber, and witbier<\/p>\n<p>The red section: pilsner<\/p>\n<p>The purple section: fruitbier<\/p>\n<p>The teal section: hoge gisting<\/p>\n<p>Based on the size of the nodes, Hoge Gisting proved to be the most popular beer type.<\/p>\n<p>In future iterations, I would like to create a geospatial visualization with this data. It would be interesting to see what the most popular beers of different regions in Belgium are, and maybe which types are region-specific.<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Belgium is famous for many things: waffles, fries, and chocolate among them. But beer is probably at the top of the list.\u00a0The Delirium Cafe in Brussels has a beer menu that more resembles a book. It contains over\u00a02,000 different brands and currently holds the Guinness World Record. In order to get a better sense of&hellip;<\/p>\n","protected":false},"author":202,"featured_media":3093,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"coauthors":[],"class_list":["post-3043","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-visualization"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paBdcV-N5","_links":{"self":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/3043","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/users\/202"}],"replies":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/comments?post=3043"}],"version-history":[{"count":0,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/3043\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/"}],"wp:attachment":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media?parent=3043"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/categories?post=3043"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/tags?post=3043"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/coauthors?post=3043"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}