{"id":3476,"date":"2017-04-26T13:21:31","date_gmt":"2017-04-26T18:21:31","guid":{"rendered":"http:\/\/commons.trincoll.edu\/amst-data-driven\/?p=3476"},"modified":"2017-04-28T15:07:35","modified_gmt":"2017-04-28T20:07:35","slug":"presentation-lab","status":"publish","type":"post","link":"http:\/\/commons.trincoll.edu\/amst-data-driven\/2017\/04\/26\/presentation-lab\/","title":{"rendered":"presentation lab"},"content":{"rendered":"<p>The graphs from the labs each have their own place of importance. Together, they show everything about the conversation regarding #alternativefacts. In the second lab, we used Carto to see the geography surrounding the conversation. Out of my 72 tweets with locations, 70 were located in the United States. The other two were from western Europe.<\/p>\n<p>In the next lab, we used text analysis to really break down what the conversation was at the core. These results showed that most of the conversation was about Trump, fake news, and decisions the Trump administration had made. It also showed that Sean Spicer and an account with the handle &#8220;killerbee805&#8221; controlled most of the conversation. Other common words were &#8220;nobannowall&#8221; and &#8220;theresistance&#8221;.<\/p>\n<p>In the fourth lab, we showed how all of the conversation is connected. In the center of my SNA, &#8220;alternative facts&#8221; was right in the center with a large circle showing that all of the tweets in the conversation relate back to alternative facts. There are two other large phrases connected which are &#8220;realdonaldtrump&#8221; and &#8220;sean spicer&#8221; These two are closely connected to alternative facts. There are many small other dots circles and lines that are intertwined and surrounding these. As a whole, it appears to be a very large, but perfect circle around the outside.<\/p>\n<p>Finally, we dissected the languages. My tweets were in English 89.7% of the time. The other 10% of the tweets were made up of\u00a0ca, de, en, fr, it, ja, nl, pt, ru, sv, tr, uk and zh-cn. A majority of them are Russian. When comparing days of tweets, there was quadruple the number of tweets one day compared to the other. This was because on 1\/6\/17 (the more tweeted day) News broke of Russian ties, the Mexican boarder and who was being selected in Trumps Cabinet.<\/p>\n<p>When everything is tied together, it is easy to see that almost all of the tweets are coming from the US and are entirely related to President Trump. (That still sounds absurd) It also explains why Spicer is a large majority of the conversation. It shows the focus on the Trump administration and their decisions. Most of the tweets are mocking or going against him. It is interesting to see how much it is being talked about. There was a significant about of tweets everyday.<\/p>\n<p>The two most influential graphs are the SNA and the word cloud because they show who is talking and what is most commonly being talked about.<\/p>\n<p>&nbsp;<\/p>\n<p>Argument<\/p>\n<ul>\n<li>how and why all of the graphs and research connect to build a larger picture and what this picture means = what are alternative facts in the era of big data?<\/li>\n<li>all my data is about Trump, his administration, and their decisions as a whole<\/li>\n<li>most tweets are located in the US and in English\n<ul>\n<li>explain why<\/li>\n<\/ul>\n<\/li>\n<li>alternatfacts, spicer and killerbee805 &#8211; they run most of the conversation<\/li>\n<li>why are the words from the word cloud there\n<ul>\n<li>why are they important<\/li>\n<li>how they are important<\/li>\n<\/ul>\n<\/li>\n<li>SNA\n<ul>\n<li>who is talking<\/li>\n<li>who are they talking to<\/li>\n<li>what is being said\n<ul>\n<li>common terms and such<\/li>\n<\/ul>\n<\/li>\n<li>how it all connects.<\/li>\n<\/ul>\n<\/li>\n<li>Why is this relative to todays world<\/li>\n<li>Find a good reading to connect to* that brings it all together<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The graphs from the labs each have their own place of importance. Together, they show everything about the conversation regarding #alternativefacts. In the second lab, we used Carto to see the geography surrounding the conversation. Out of my 72 tweets with locations, 70 were located in the United States. The other two were from western&#8230;<\/p>\n","protected":false},"author":1776,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[13],"tags":[],"_links":{"self":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3476"}],"collection":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/users\/1776"}],"replies":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/comments?post=3476"}],"version-history":[{"count":1,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3476\/revisions"}],"predecessor-version":[{"id":3534,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3476\/revisions\/3534"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=3476"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=3476"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=3476"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}