![\"Screen](\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/04\/Screen-Shot-2017-04-11-at-2.50.20-PM.png\")
<\/p>\n32 languages: Ar, Bg, ca, Cs, Da,De,El,En,En-gb, Es, Fr, he, hr, hu, id, it, ja, Ko, lv, nl, no, pl, pt, ru, sr, sv, th, tr, vi, xx-lc, Zh cn, & Zh tw<\/p>\n
65,660 en tweets out of 75620. 86.8% are in English.
\nGerman: .4% and Armenia: .07%
\nThe current president of the US is a global topic, it makes sense that around 13% of the tweets are in a different language. It is obvious that the largest percentage should be in English, but I thought a bigger percentage would be German, given how much they like to compare his policies to one of a former German leader. Even given the internationality of this issue, I would not have been surprised if the percentage of english tweets using this hashtag were be above 95%.<\/p>\n
<\/p>\n
![\"Screen](\"http:\/\/commons.trincoll.edu\/amst-data-driven\/files\/2017\/04\/Screen-Shot-2017-04-11-at-3.08.35-PM.png\")
<\/p>\n
By day: it is a pretty even distribution of tweets per day during the 2 weeks of Feb where my dataset is from. The first and last day may have less because they are incomplete (one started late and the other ended early). There were no significant spikes in the tweets.<\/p>\n
Feb 1: Washington Post reports \u201cDonald Trump had his first good day\u201d as president. He selected his supreme court nominee on this day.
\nFeb 2: The Frederick Douglas fiasco
\nFeb 3: News reports say that Trump\u2019s immigration ban was blocked on this day.
\nFeb 4: America\u2019s sweetheart, Angelina Jolie, speaks out against Trump\u2019s immigration ban. The second greatest thing she\u2019s ever done, right behind her portrayal of Lara Croft in Tomb Raider.
\nFeb 5: Politico magazine posts great article about the First Lady and her role as a supporting wife.
\nFeb 6: Trump unwelcome at British parliament. Also Kanye West doesn\u2019t like Trump either!
\nFeb 7: Iranian leader calls Trump \u201cthe real face of the US\u201d
\nFeb 8: Nordstrom drops the first lady\u2019s clothing line from their selection.
\nFeb 9: The Economist reports that Trump\u2019s actions are helping Islamic radical groups
\nFeb 10: BBC reports president Trump is considering a new travel ban, this following his earlier attempt was unsuccessful.
\nFeb 11: Judges uphold suspension of \u2018travel ban\u2019
\nFeb 12: An article is published about the immigration of refugees from America to Canada to escape Trump
\nFeb 13: Thousands of Mexicans protest wall and ban
\nFeb 14: An economist warns of impending doom under Trump\u2026 what else is new?
\nFeb 15: Trump\u2019s nominee for labor secretary withdraws from position<\/p>\n
With all this happening, the tweets stayed pretty consistent across these two weeks. Maybe there was just always something going on, so there were always people tweeting. It is also worth considering the fact that the hashtag #MakeAmericaGreatAgain usually is used for pro-Trump tweets, and much of this news was negative so it\u2019s likely that the supporters didn\u2019t want to tweet about it. I wish that my data had significant spikes in it, so I could go back and analyze what was happening. That would be very cool, and it would bridge the final divide between data and real life. There is a mini spike at 2\/13, the day of the Mexican protests. <\/p>\n
I had one of the higher means and medians in our class, so clearly this topic was getting a lot of internet traffic. The fact that my mean and median are so close shows that my data itself has few outliers and works to balance itself out across the 2 week time period. I think my data stands out a little bit in terms of amount of tweets or sheer volume but I like that it is consistent. This means that my hashtag is popular, but it stays the same amount of popular throughout the time span. <\/p>\n
My data reveals that while I am high on the total tweets I am relatively average on everything else. I had a greater number of tweets, but proportionally I was about the same for my other numbers. It is normal with more tweets to have higher mins and maxs, so I don\u2019t see this as alarming or cool. I was not at all a standout in this department. This hashtag is pretty steady in the amount of hits it gets from day to day, and it does not rise and fall like a wave. The high range can be attributed to the incomplete days that start and end my time period.<\/p>\n
For me the descriptive statistics don\u2019t really change how I view the graph. Like my mentor Yau, I am focused on the meaning behind the data and married to the idea that collecting numerical information about the real world can only tell a part of the story. My mind is not easily swayed, and this additional collection of meta-data doesn\u2019t quite do it for me. <\/p>\n","protected":false},"excerpt":{"rendered":"
32 languages: Ar, Bg, ca, Cs, Da,De,El,En,En-gb, Es, Fr, he, hr, hu, id, it, ja, Ko, lv, nl, no, pl, pt, ru, sr, sv, th, tr, vi, xx-lc, Zh cn, & Zh tw 65,660 en tweets out of 75620. 86.8% are in English. German: .4% and Armenia: .07% The current president of the US is…<\/p>\n","protected":false},"author":1665,"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\/3303"}],"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\/1665"}],"replies":[{"embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/comments?post=3303"}],"version-history":[{"count":3,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3303\/revisions"}],"predecessor-version":[{"id":3308,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3303\/revisions\/3308"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=3303"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=3303"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=3303"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}