The U.S. population is racially diverse- a characteristic necessary for racial injustice. So, I expect that the majority of #BlackLivesMatter tweets to be from 30N-40N and 90W-150W — the United States. I am interested to see if #BlackLivesMatter tweets were pulled from my home town at 40N 95W (if I were to guess our coordinates).<\/p>\n
To date, 83935\u00a0tweets were pulled from Twitter.<\/p>\n
I have 131 mappable tweets, which means that 0.16% of the tweets have geolocations. Nathan Yau, in his book Data Points, writes about the importance of telling the story that we intend to tell with data. Therefore, it is necessary for me to mention that the map of #BlackLivesMatter tweets (below) is by no means an accurate depiction of support of the Black Lives Matter movement throughout the world. Rather, the map below is an investigation of mappable data and data visualization. From the geolocations that are available, 30W-40N 70W-90W, \u00a0I expect most of the tweets to be from the U.S. Moreover, all but about 10 tweets are written in English. I expected most of the tweets to be in English, because to my knowledge most black people in the U.S. speak English.<\/p>\n
Of all of the hashtags being monitored in class, #BlackLivesMatter, with roughly 83,000 tweets, ranked second in most number of tweets. This would suggest that the set of #BlackLivesMatter tweets is big data. However, Kate Crawford, in Think Again: Big Data<\/em>, writes that\u00a0“there are “signal problems” in big-data sets — dark zones or shadows where some citizens and communities are overlooked and underrepresented.” So it is possible that some of the people who would be of interest to study, people of color in poor urban areas, may not be represented in my data set. This is of particular concern since #BlackLivesMatter is heavily concerned with people of color in poor urban areas. Crawford also writes that “only 16 percent of online adults in the United States use Twitted, and they are by no means a representative sample — they skew younger and more urban than the general population.” This fact suggests that the “dark zones or shadows” of big data may not affect as severely a study of young urban people. It is obvious that the data collected needs to be studied further before it can be concluded that the data is “good data”.<\/p>\n The other hashtags on my team are #noDAPL and #woke. To date,\u00a0#noDAPL has 27,000 tweets and\u00a0#woke has 11,500. Perhaps #BlackLivesMatter has 4-8 times the number of tweets, because injustices covered by\u00a0#BlackLivesMatter are long standing. The Black Lives Matter movement began in 2013, and continues to be a addressed in the news and on social media. On the other hand, #woke is more of a trend than a movement. As for the Dakota Pipeline, my guess would be that #MuslimBan has overshadowed #noDAPL.<\/p>\n\n\n