{"id":2737,"date":"2017-03-04T02:19:10","date_gmt":"2017-03-04T07:19:10","guid":{"rendered":"http:\/\/commons.trincoll.edu\/amst-data-driven\/?p=2737"},"modified":"2017-05-01T00:42:48","modified_gmt":"2017-05-01T05:42:48","slug":"meaning-behind-the-words","status":"publish","type":"post","link":"http:\/\/commons.trincoll.edu\/amst-data-driven\/2017\/03\/04\/meaning-behind-the-words\/","title":{"rendered":"Meaning Behind the Words"},"content":{"rendered":"

There is a story amongst the data points that I have collected through my software. To be thorough in the conduction of this research, it is important to analyze the actual content of the tweets in the set. I have changed the hashtag for this post to #FakeNews because of the lack of volume delivered by #DataRefuge. In the text analysis, I hope to hear\u00a0a lot within the United States about reported news that the American people find untruthful. Perhaps I’ll see the word “Truth” at the forefront of the text analysis, as most people are eager to hear the truth and nothing but the truth when receiving information on contemporary matters especially.<\/p>\n

This word cloud totals 748,952 words and has some unique ones that are interesting to look more into, such as “#extremevetting” and “#therealdonaldtrump”. I’m interested to see how the hashtag interacts with the commonly tweeted words. For example, one tweet says “Breaking News: Trump reiterates\u00a0that he is “SO MAD” about ruling on travel ban.” I wonder how the fake news hashtag corresponds to this. After stopping words that are obvious to be seen, there is a new group of words that stands out in the cloud and it is conceivable that these words would. Note the large presence in “cnn” and “muslim”. CNN is leading the charge in many accusations of “fake news” by the Trump administration. When it comes to “muslim”, I am super interested in seeing how fake news ties in because I have my own opinion on this. It is fake news when the media targets this availability heuristic in humans by classifying muslims\u00a0to one specific look, behavior and social light. With the media being a main source of information, this negative light promulgates through social consensus and further exacerbates the irrational islamophobic issue in our world. I think that conspiracy is missing as well as “antimedia”. I do believe the media is immensely influential in the charging of human opinion, therefore there are obviously many people against the corporate approach.<\/p>\n

Some of the words are completely obstructive, such as “it’s”, “bfraser747”, “necea”, “a”, “isn’t”, etc. To aid in the analysis, these words will be added to the Stopword list. I included 225 words in the cloud to tell the best story possible. The idea is that the volume of words explains how many people are talking about this topic and there are many words that are the same size which explains that many consumers of media are bias against fakenews for a myriad of specific reasons. I expected to see ‘Trump’ moreso than any other term because it is evident that while people may have been anti-media, he has shed much light on the idea of the media being untruthful. Whether people agree or disagree with his comments, it is naturally he who is the root of most of the tweets. The five most frequent terms are ‘trump’, ‘cnn’, ‘news’, ‘realdonaldtrump’\u00a0and ‘media’. The overarching idea is the hashtag ‘#fakenews’ is politically charged and continuous with media, and media is non-stop. Refer to word cloud below:<\/p>\n

\"word<\/p>\n

Aforementioned, Donald Trump has been a main term that shows up in my word cloud. Similarly, CNN and even WikiLeaks. I mentioend why Donald Trump is so frequently spoken of as well as CNN. It seems that CNN will get most of the lash from the Trump administration being the liberal news netowrk they are. WikiLeaks was not as frequently talked about but it is interesting to determine whether or not they believe WikiLeaks is fake or if WikiLeaks is proving that news is fake. Speaking of word frequency, it is important to take a look at word trends as well. See below:<\/p>\n

\"Capture\"<\/p>\n

This does not surprise me considering this was the time frame in which the travel ban was just starting to be talked about. You can see the spikes in ‘CNN’ whenever Donald Trump made an executive order.<\/p>\n

http:\/\/voyant-tools.org\/?corpus=72cfe4e5838b525a0e50ac1f8264d701&stopList=keywords-415b91c1f6d5db0b5b7b5b2b05c526a3&panels=corpusterms,reader,trends,summary,contexts<\/p>\n

I chose the article “With Facebook, Blogs and Fake News, Teens Reject Journalistic Objectivity”. I chose this because I feel this article pertains to the student body at Trinity College especially. This idea states that adolescents, as represented by a racially diverse group of students across high schools in America in this study, prefer opinionated news rather than objective news. This segues perfectly into this idea of “fake news” which may not be that the information is absolutely inaccurate but the veracity of the opinions behind the information could be weak. This type of lackluster dissemination caters itself to misinformation. After uploading this article into the word cloud software, I chose to stop the words:\u00a0news, media, information, new, people.<\/p>\n

 <\/p>\n

\"Capture\"<\/p>\n

 <\/p>\n

This word cloud is especially interesting because it seemed as if it was the older generation who were keeping our traditionally conservative beliefs anchored in our society in a way that generated fake news. However, it seems to be that the world is talking about how fake news is aligned with adolescents and our preference to listen and be manipulated by radical opinions.<\/p>\n

Lastly, we refer to Tufte and Yau. Their quotes directly relate to my hashtag and it will be easy to connect them to my works. Tufte quotes,\u00a0\u201cSuperior methods are more likely to produce truthful, credible, and precise findings\u201d (1997, 27). \u00a0Yau quotes,\u00a0\u201cData is an abstraction of real life, and real life can be complicated, but if you gather enough context, you can at least put forth a solid effort to make sense of it\u201d (2013, 41). In the context of my hashtag, Tufte has a more connected point. If you have the best method or approach you are the most likely to produce truthful, credible and precise findings. If a news outlet has the most superior method, then that means they are let into the guts of the story and put effort towards making sense of all of it through the contextual evidence. This segues perfectly into Yau’s quote as it speaks off making sense of context. This is where it can get tricky. Fake news is said to be the opinionated version of a story. One can gather context yet somehow if enough bias is present, the story will be skewed.<\/p>\n

The media is a major source of corruption within the United States, not because of their stories necessarily, but because of their microcosmic divide amongst networks themselves. They lack the necessary paradigm our country needs.<\/p>\n","protected":false},"excerpt":{"rendered":"

There is a story amongst the data points that I have collected through my software. To be thorough in the conduction of this research, it is important to analyze the actual content of the tweets in the set. I have changed the hashtag for this post to #FakeNews because of the lack of volume delivered…<\/p>\n","protected":false},"author":1160,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/2737"}],"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\/1160"}],"replies":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/comments?post=2737"}],"version-history":[{"count":10,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/2737\/revisions"}],"predecessor-version":[{"id":3805,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/2737\/revisions\/3805"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=2737"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=2737"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=2737"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}