{"id":3103,"date":"2017-03-31T15:25:54","date_gmt":"2017-03-31T20:25:54","guid":{"rendered":"http:\/\/commons.trincoll.edu\/amst-data-driven\/?p=3103"},"modified":"2017-03-31T15:25:54","modified_gmt":"2017-03-31T20:25:54","slug":"graphing-2a","status":"publish","type":"post","link":"http:\/\/commons.trincoll.edu\/amst-data-driven\/2017\/03\/31\/graphing-2a\/","title":{"rendered":"graphing #2a"},"content":{"rendered":"<p>I selected my data from the beginning of February, February 1st to be exact, since my topic was heavily discussed around this time, thus there will be a significant amount of more relevant tweets to my topic regarding proposals made by the government. The number of tweets I am using is around 4,000. When selecting #1 on the t2g.py file, I am expecting to see a great number of retweets and their contents dominating the map since the majority of my tweets are retweets. After running the python script, I have 7586 lines.<\/p>\n<p>When opening the Le Mis example file, i noted 77 nodes and 254 edges. Undirected graph would work better than a directed graph to express relationships between characters rather than conversations, allowing to see the amount each character relates to each other rather than just their conversations to one another.<\/p>\n<p><img loading=\"lazy\" class=\"alignnone size-medium wp-image-3105\" src=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.25.39-PM-300x211.png\" alt=\"Screen Shot 2017-03-31 at 3.25.39 PM\" width=\"300\" height=\"211\" srcset=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.25.39-PM-300x211.png 300w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.25.39-PM-768x541.png 768w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.25.39-PM-1024x721.png 1024w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.25.39-PM.png 1530w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>&nbsp;<\/p>\n<p>Valjean has the ID #11. Fantine has ID #23. Valjean targets ID #&#8217;s 0,2,3,and 10. Fantine targets ID# 11,12,16,17,18,19,20,21, and 22.<\/p>\n<p><img loading=\"lazy\" class=\"alignnone size-medium wp-image-3112\" src=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.48.27-PM-300x211.png\" alt=\"Screen Shot 2017-03-31 at 3.48.27 PM\" width=\"300\" height=\"211\" srcset=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.48.27-PM-300x211.png 300w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.48.27-PM-768x540.png 768w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.48.27-PM-1024x720.png 1024w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Screen-Shot-2017-03-31-at-3.48.27-PM.png 1530w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>compared to the previous graph, it appears that the groups have become more clustered and centered around each other rather than intermixed with other nodes.<\/p>\n<p>When setting the betweenness centrality, I believe it will increase the size and weight of the nodes based off of relevance.<\/p>\n<p><img loading=\"lazy\" class=\"alignnone size-medium wp-image-3122\" src=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Lesmis2-300x300.png\" alt=\"Lesmis2\" width=\"300\" height=\"300\" srcset=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Lesmis2-300x300.png 300w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Lesmis2-150x150.png 150w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Lesmis2-768x768.png 768w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Lesmis2-380x380.png 380w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/Lesmis2.png 1024w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>For my own gephi\u00a0graph, I chose to use a repulsion of 10,000 since there is\u00a0a large amount of nodes represented. My average path length was 4.752, which I believe means the relevance between nodes and the confidence factor of each pathway. The connected components is 375, meaning I have 375 connected groups. The modularity is .816, meaning the strength of the ties the nodes have within each group.<\/p>\n<p><img loading=\"lazy\" class=\"alignnone size-medium wp-image-3129\" src=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/2a_2-300x300.png\" alt=\"2a_2\" width=\"300\" height=\"300\" srcset=\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/2a_2-300x300.png 300w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/2a_2-150x150.png 150w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/2a_2-768x768.png 768w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/2a_2-380x380.png 380w, http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/03\/2a_2.png 1024w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>It is hard to see the connections in this graph since there are a lot of small nodes with a degree of only one or two. surprisingly, this is still the graph after changing the degree to at least 5! Analyzing the Big purple group (NRA) and the blue group (SenatorSessions), I can see a lot of commonality with the tweets between these two twitter handles. perhaps during this period of time Senator Sessions was advocating for something relating to gun control? It seems as if the majority of my groups are big retweeters in the twitter community\u00a0since the majority of group names are specific twitter handles.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I selected my data from the beginning of February, February 1st to be exact, since my topic was heavily discussed around this time, thus there will be a significant amount of more relevant tweets to my topic regarding proposals made by the government. The number of tweets I am using is around 4,000. When selecting&#8230;<\/p>\n","protected":false},"author":1789,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[6],"tags":[],"_links":{"self":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3103"}],"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\/1789"}],"replies":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/comments?post=3103"}],"version-history":[{"count":1,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3103\/revisions"}],"predecessor-version":[{"id":3131,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3103\/revisions\/3131"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=3103"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=3103"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=3103"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}