{"id":3179,"date":"2017-04-12T11:48:39","date_gmt":"2017-04-12T16:48:39","guid":{"rendered":"http:\/\/commons.trincoll.edu\/amst-data-driven\/?p=3179"},"modified":"2017-04-12T15:19:22","modified_gmt":"2017-04-12T20:19:22","slug":"3179","status":"publish","type":"post","link":"http:\/\/commons.trincoll.edu\/amst-data-driven\/2017\/04\/12\/3179\/","title":{"rendered":"Breaking down #2a"},"content":{"rendered":"

I am using the twitter data from 2\/01\/17 in order to compare against previous lab results and to stay consistent. When sorting out the data by user_lang, I noticed a decent amount of languages used, being bg, da, de, en, en-gb, es, fr, id, it, ja, lv, nl, pl ro, ru, and su. After running the countif function, I have a total of 4450 tweets in English. Out of a total of 4790 tweets, the percentage of tweets in English is 93%.<\/p>\n

\"%ofTweets\"<\/p>\n

I am not surprised most of my data is in English because this topic is related only to the United States, a primarily English speaking country. I noticed that most of the Russian tweets were retweets translated by the same twitter user named Slava381977. There were very few French tweets, only 7 to be exact, and the other tweets account for less than 1% of my twitter data, so it is safe to assume most of my tweets are in English.<\/p>\n

\"bargraph\"<\/p>\n

Since my selection of data was only during a period of a day, I broke down the tweets into the number of tweets per hour. The most prominent times for people to be tweeting are around 5AM and 10PM. I am not sure why there were no recorded tweets from 7 AM to 1PM, it could have been an issue with the collection of tweets where I cut off the data stream prematurely. I understand why there was such heavy use at 10PM, because during this time the television show Sean Hannity is on where he discusses very controversial topics. The data is from when U.S. Attorney\u00a0General Jeff Sessions was nominated for his current position, and it was a very controversial nomination since he is very pro-Second Amendment rights. Fox &Friends is on tv from 4-6AM, so this could be the possible reason for a heavy number of tweets at 5AM. Another reason for heavy traffic between 5-6AM is this could be when most people wake up and they want to tweet about something. Aside from the missing data, the flow of tweets seems common, with not a lot of tweets in the middle of the day, and heavy use in the morning and night.<\/p>\n

\"Screen<\/p>\n

The data above only represents hours when data was collected, meaning the period where no tweets were recorded are not included. Having an average of 282 tweets per hour is great because it is not far from the median of 286, meaning there are not too many outliers in my data. This is great because it means the data is consistent throughout the day, even during peak and downtimes. I was surprised to have a mode value since it is rare for there to be the same amount of tweets in two different hours. Having the same median and mode is interesting, with the most common value being the same as the exact middle value. My biggest takeaway from these numbers\u00a0is my data is consistent rather than a large amount being collected in a small amount of time. Since my tweets are being sorted by hour instead of by day, it is tough to compare my tweets to the class data.<\/p>\n

Having a max of 391 and min of 169 helps show the consistency of collection of my data since it shows the downtime of collection still had a reasonable amount of tweets, and the peak was not a considerable increase. with a range less than the average at 222, helping to show the consistency of my data. One thing I have noticed is the majority of tweets in Russian occur from 1AM to 5AM, showing there was no real downtime for my hashtag. It is surprising to see the quantity of tweets from Russia relating to my hashtag since it is regarded a United States issue rather than a global issue. The reason for the tweets could be for the same reason stated above regarding Jeff Sessions nomination.<\/p>\n","protected":false},"excerpt":{"rendered":"

I am using the twitter data from 2\/01\/17 in order to compare against previous lab results and to stay consistent. When sorting out the data by user_lang, I noticed a decent amount of languages used, being bg, da, de, en, en-gb, es, fr, id, it, ja, lv, nl, pl ro, ru, and su. After running…<\/p>\n","protected":false},"author":1789,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[11],"tags":[],"_links":{"self":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3179"}],"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=3179"}],"version-history":[{"count":3,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3179\/revisions"}],"predecessor-version":[{"id":3278,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/posts\/3179\/revisions\/3278"}],"wp:attachment":[{"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/media?parent=3179"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/categories?post=3179"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/commons.trincoll.edu\/amst-data-driven\/wp-json\/wp\/v2\/tags?post=3179"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}