{"id":3442,"date":"2017-04-27T13:58:50","date_gmt":"2017-04-27T18:58:50","guid":{"rendered":"http:\/\/commons.trincoll.edu\/amst-data-driven\/?p=3442"},"modified":"2017-04-28T14:58:36","modified_gmt":"2017-04-28T19:58:36","slug":"outlining-and-refining-my-isis-presentation","status":"publish","type":"post","link":"http:\/\/commons.trincoll.edu\/amst-data-driven\/2017\/04\/27\/outlining-and-refining-my-isis-presentation\/","title":{"rendered":"Outlining and Refining my #ISIS Presentation"},"content":{"rendered":"<p>While each of our graphs are entirely unique to the hashtag we have studied\u00a0throughout the semester, comparing these visualizations furthers our understanding of our data.\u00a0We were able to draw more effective conclusions on some of these visualizations as compared to others, however all of these graphs provided some insight. It was interesting to see which methods represented each of our data sets best.<\/p>\n<p>In making these comparisons, I felt that the word cloud did revealed the most about each of our data sets. These visualizations effectively portrayed the discussion surrounding our hashtag topics, delving deeply into the nuances of each of our individual subjects. The word graphs that we made during the same lab as the word clouds were also telling of our hashtag topics. Each of our word graphs showed that the prevalence of certain words in our tweets was highly variable on a day to day basis. I believe that this is revealing of the situation in the Middle East, where military maneuvers and attacks fluctuate, and drum up a significant amount of media attention. The combination of these graphs in Voyant was effective in showing both the backbone topics that facilitate discussion on our issues as a whole, as well as how the focus of these conversations may pivot depending on what is happening in the media.<\/p>\n<p>Similarly, it was interesting to look at the graph of tweets per day, as they were also reflections of military maneuvers and attacks. In this sense, I believe my graph would correlate more directly with Ian&#8217;s, as the subjects of ISIS and Syria are more likely to be discussed following attacks. While Nell&#8217;s topic of the Muslim ban certainly had a correlation with these events, her tweets were also influenced by other discussions of American politics.<\/p>\n<p>Another interesting data representation was the SNA graph, which showed the geolocations of our tweets. I was surprised to find that while each of us collected huge amounts of tweets (the most in the class overall), each of us had very few mappable geolocations. My map only showed a dozen geolocations despite me having collected nearly one hundred thousand tweets at the time. This could be due to the diverse nature of the areas in which our tweets were coming from, as some areas may have different policies regarding geolocation, or lack the technology or software to track the tweets.<\/p>\n<p>My hypothesis as to the very limited hits on geolocation is directly related to what we found when looking at the languages of our tweets. My tweets came from a vast variety of languages, so one can logically assume they were coming from a huge variety of countries as well. I thought it was very cool to see how global our topics were, and I once again believe this is due to the inherent nature of conversations regarding the Middle East.<\/p>\n<p>Key Argument of Presentation:<\/p>\n<ul>\n<li>I plan to argue that the vast global attention to the topic of #ISIS had a significant on my data and findings\n<ul>\n<li>I will argue that because it is so globally discussed, my data was consistently pouring in, and consisted of a wide variety of languages from many different countries<\/li>\n<\/ul>\n<\/li>\n<li>In addition to this, I will argue that my unlike many of the other topics which tend to be debated, there is a general consensus that ISIS is a terrible organization.\n<ul>\n<li>This leads to the diversity in my dialogue stemming not from two different sides to an issue, but rather how the issue impacts people based on where they are on the globe\n<ul>\n<li>Ex: Tweets from first hand experiences in the Middle East, vs. Tweets coming from the American perspective, vs. tweets from other countries who are involved in different ways.\n<ul>\n<li>Each lens provides and interesting opportunity to grip the issue on the whole.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li>Finally, I will argue that while I consistently had a baseline flow of tweets, the fluctuations in my data correlate directly with attacks in the Middle East\n<ul>\n<li>Not only is ISIS so frequently in the news for violent acts they have committed, they are also the first to be blamed for unprecedented attacks as whole\n<ul>\n<li>They receive a significant amount of publicity due to this, which is interesting given how much they thrive off of it.\n<ul>\n<li>They use social media and Twitter as a means of recruiting, this high influx of tweets only furthers the message they are trying to send<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>While each of our graphs are entirely unique to the hashtag we have studied\u00a0throughout the semester, comparing these visualizations furthers our understanding of our data.\u00a0We were able to draw more effective conclusions on some of these visualizations as compared to others, however all of these graphs provided some insight. It was interesting to see which&#8230;<\/p>\n","protected":false},"author":1680,"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\/3442"}],"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\/1680"}],"replies":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/comments?post=3442"}],"version-history":[{"count":4,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3442\/revisions"}],"predecessor-version":[{"id":3569,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3442\/revisions\/3569"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=3442"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=3442"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=3442"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}