{"id":2583,"date":"2017-03-03T15:09:10","date_gmt":"2017-03-03T20:09:10","guid":{"rendered":"http:\/\/commons.trincoll.edu\/amst-data-driven\/?p=2583"},"modified":"2017-03-03T20:55:06","modified_gmt":"2017-03-04T01:55:06","slug":"what-do-you-have-to-say-about-that","status":"publish","type":"post","link":"http:\/\/commons.trincoll.edu\/amst-data-driven\/2017\/03\/03\/what-do-you-have-to-say-about-that\/","title":{"rendered":"What do you have to say about that?"},"content":{"rendered":"

Considering my research and the content of the tweets I have collected related to #keystoneXL, I am hoping to see words generally related to the resistance movement for construction of the pipeline. Words I expect to see are “dapl” or “transcanada” or “standing rock” which all are directly affected by this hashtag and seems to come up frequently throughout the tweets I have collected.<\/p>\n

The 10 documents I had organized for my Twitter data found a total of 251,935 words and 27,578 unique words. Some of the most frequent words that were found was “keystonexl,” “daps,” “pipeline,” and “nodapl.” Some of the interesting data points found from the summary box was that in document February 21-23rd one of the usual words selected was “water protectors” and in the document for February 9-11th the term “price of oil” I found unique. I also found the phrase “baxter bean” and “apcentralregion” to both be really common, which I later found are both Twitter handles, “apcentralregion” being a a news organization in Texas and midwest region of the US and “baxter bean” referencing an individual who frequently expresses their interest in political and environmental issues.\u00a0The words that stand out first within the text analysis image were “american,” “pipelines,” “jobs,” and “Trump” all which really encompass the general beliefs and tweets I have found in association with the hashtag. Furthermore, these specific words really focus on\u00a0the american-pro side of this issue rather than the real debate that I feel like is occurring between the people who are being affected by the issue.\u00a0Some unusual phrases or words that I found to be used were like “ilz4mme” or “kgrumke” which I assume are Twitter handles that are repeated when people retweet the same tweet frequently. Other phrases that didn’t make much sense in the context were like “puts,” “it’s,” “haven’t,” “hey,” and “oh.”\u00a0<\/strong><\/p>\n

Words I included in my stop list:<\/p>\n

    \n
  1. ilz4mme<\/li>\n
  2. just<\/li>\n
  3. kgrumke<\/li>\n
  4. hasn’t<\/li>\n
  5. that’s<\/li>\n
  6. you’ve<\/li>\n
  7. today<\/li>\n
  8. tens<\/li>\n
  9. mid<\/li>\n
  10. puts<\/li>\n
  11. lots<\/li>\n
  12. it’s<\/li>\n
  13. haven’t<\/li>\n
  14. oh<\/li>\n
  15. is6ryztyq7<\/a><\/li>\n
  16. \u0444\u043f<\/a><\/li>\n<\/ol>\n

    I included a total of 155 words in order to really visualize entirely what the data I have collected thus far is saying. With only a bit over 10,000 tweets for #keystoneXL, I am hoping to extrapolate as much as I can from such a condense set of data.<\/p>\n

    The cirrus cloud shows the debate of the Keystone XL project as a whole. The words like Trump, American, pipelines, no DAPL, DAPL, oil, create and jobs are all centered within the image from being the most popularly tweeted and happen to really channel the pro-side of this issue that has been argued persistently throughout this debate. However, the smaller words in the background, like blocked, nebraska, lied, pollute, bulldozing, resistance and protestors all really speak to the doubts and concerns many people have about this issue, and symbolize their voices being minimally heard and taken into account as the project continues to charge forward. I was surprised to see words like canada, alberta, prosperity, truth out and applauded. It’s really interesting and cool to see how these words clash with one another\u00a0while still clumped together like they represent a cohesive population or topic,\u00a0when in fact it represents the\u00a0reality that this\u00a0project\u00a0starkly separates the population. The text analysis below is consistent with what I have been finding in terms of the different arguments that have been revealed throughout my Twitter data and smaller side-arguments for the issue will hopefully come up in later analysis in order to see how it frames the debate for the Keystone XL project and creates the picture below.<\/p>\n

    \"Screen<\/p>\n

    The three big words that I wanted to explore further were National Resources Defense Council (NRDC), no DAPL, and jobs. All three of these terms were very popular throughout my collected Twitter data, but also again really encompass the argument against the Keystone XL project and show how protestors of the XL project rally behind these main points to further propel the resistance of its construction. Furthermore, I thought it would be really interesting to see where these main protesting points for the XL project fluctuate throughout time in relation to one another.<\/p>\n

    \"Screen<\/p>\n

    It is interesting to see that the words NRDC and no DAPL run pretty similar together for the middle\u00a0two weeks of February, but at the beginning of February no DAPL and jobs were more similar. Then towards the last week of February no DAPL grew in frequency higher than any of the other words had reached, and once it calms down, the NRDC spikes up with jobs taking off as well. It doesn’t surprise me that there is such low frequencies of NRDC and no DAPL throughout the middle of February since there was little acceleration in the project occurring during that time and less was being tweeted in general. I think it’s interesting that jobs however remained some popularity throughout that middle part of February however and wonder what was propelling that word to be used more than the others. I also find it interesting why the no DAPL peaked between February 18th and the 24th, indicating a political advancement must have taken place to move forward with the Dakota access for the pipeline.<\/p>\n

    http:\/\/voyant-tools.org\/?corpus=544ab8df4fe74917b10c44a0d1c8489e&stopList=keywords-576b894e1bfa8b47c5594ad5331d7c21&panels=cirrus,reader,trends,documents,contexts<\/p>\n

    I chose an article published in the New York Times called Game Over” for the Climate: The Keystone XL Pipeline on TV News\u00a0<\/em>written by Elisabeth Wilder. While this document is actually 90 pages long, it does a great job going beyond the general outline of what the project is\u00a0and delves into the environmental influences the project has on all of America, not only those directly impacted with its construction. Given that most of America is on board with the XL project, Wilder analyzes what the media is reporting and their methods that recruit such large support for this pipeline extension. Wilder even makes the point that the media heavily relies on the government and businesses as their sources, thus broadening and channeling news related to Keystone XL to be reported in a more political and economic lens. This helps to explain why I have been collecting a large amount of tweets that are more political and force the data to make it appear that the topic is less environmentally presented.<\/p>\n

    \"Screen<\/p>\n

    http:\/\/voyant-tools.org\/?corpus=68c5b72ad84ed28df9e1b5bb0226aec4&panels=cirrus,reader,trends,summary,contexts<\/p>\n

    There are a lot of similarities with the data set derived from this article and with the data set I have collected from Twitter. However, Wilder’s data set touches more on the side of the media influence and the environmental perspective\u00a0that circulate around this project whereas my Twitter data set touches more on the political perspective\u00a0of the XL project. I think this data set offers a really interesting side of the topic derived from my data as much of the environmental or media perspectives of the XL project are hidden in the shadows of the political advancements and debates related to the project throughout a social media platform. I think its important to keep in mind that my Twitter data is not the Keystone XL debate in of itself, that there are many other sides to this issue that are overlooked or veiled by using the methods and analyzing the audience we are founding our research on.<\/p>\n

    While Tufte believes that methods of data collection and analysis can accurately and precisely draw conclusions on the real life issue or topic entirely, Yau believes that data collection and analysis is generally an “abstraction of real life” and can help draw conclusions on an\u00a0issue, but it doesn’t necessarily connect to the reality of a\u00a0topic in a full sense. I happen to agree with Yau considering my data on #KeystoneXL largely touches on the political perspective on the project and overshadows many other sides of this issue that rarely come up within my Twitter data. A lot of the text analysis for #keystoneXL data references words like bill, create, jobs, reported, pipeline action, sen Markey, etc that all refer to the political side-conversations about the Keystone XL project. This is also shown by the low dip in frequency of the words jobs, no DAPL, and NRDC throughout the month of February, only spiking in popularity when advancement had been made to propel the project further. Therefore, the main political focus on this issue is hiding a lot of the other focuses that shift and frame the overall debate of the Keystone XL project.<\/p>\n","protected":false},"excerpt":{"rendered":"

    Considering my research and the content of the tweets I have collected related to #keystoneXL, I am hoping to see words generally related to the resistance movement for construction of the pipeline. Words I expect to see are “dapl” or “transcanada” or “standing rock” which all are directly affected by this hashtag and seems to…<\/p>\n","protected":false},"author":1443,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[],"_links":{"self":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/2583"}],"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\/1443"}],"replies":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/comments?post=2583"}],"version-history":[{"count":18,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/2583\/revisions"}],"predecessor-version":[{"id":2736,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/2583\/revisions\/2736"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=2583"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=2583"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=2583"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}