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Geomapping Racism With Twitter
Hugh Pickens writes "Megan Garber writes that in the age of the quantified self, biases are just one more thing that can be measured, analyzed, and publicized. The day after Barack Obama won a second term as president of the United States, a group of geography academics took advantage of the fact that many tweets are geocoded to search Twitter for racism-revealing terms that appeared in the context of tweets that mentioned 'Obama,' 're-elected,' or 'won,' sorting the tweets according to the state they were sent from and comparing the racist tweets to the total number of geocoded tweets coming from that state during the same time period. Their findings? Alabama and Mississippi have the highest measures followed closely by Georgia, Louisiana, and Tennessee forming a fairly distinctive cluster in the southeast. Beyond that cluster North Dakota and Utah both had relatively high scores (3.5 each), as did Missouri, Oregon, and Minnesota. 'These findings support the idea that there are some fairly strong clustering of hate tweets centered in southeastern U.S. which has a much higher rate than the national average,' writes Matthew Zook. 'But lest anyone elsewhere become too complacent, the unfortunate fact is that most states are not immune from this kind of activity. Racist behavior, particularly directed at African Americans in the U.S., is all too easy to find both offline and in information space.'"
The SPLC does in deed execute their honorable mission. Go to http://truthy.indiana.edu/ for other meme propagation and dissemination graphics so you can see that this is one lens to the output of a much larger engine.
---- Teach Peace. It's Cheaper Than War.
How did they account for multiple racists tweets from one "tweeter"?
One racist sending 100 racist tweets is not the same as 100 different racists each sending one racist tweet each.
Reading the article it doesn't look like they bothered. And they only found a total of 395 tweets which will lead to appalling precision in any of their findings. Sadly 'information scientists' don't always appear to be the best statisticians.
Why is it irrelevant? They claim they're measuring the geolocation of racism, but only pick one very specific type.
The floatingsheep page specifically says, "we are measuring tweets rather than users and so one individual could be responsible for many tweets and in some cases (most notably in North Dakota, Utah and Minnesota) the number of hate tweets is small and the high LQ is driven by the relatively low number of overall tweets." It's not their fault that the author of the Atlantic article left out those details.
I hate to break it to you, but the press doesn't understand peer reviewed work any better. Whenever media ever looks at any academic work they completely misrepresent it. That's something you get used to.
You are right but this means that the peer review filter is even more important so that what gets out to the media and beyond has at least some chance of being right. Also, having been through the process a few times I'd say academics are at least as guilty of overstating their findings as journalists. We want the headlines and the 'impact' as much as journalists to.
LOL
You clearly did not look at the website. The guys who did this are in academia, but the website is not an academic publication nor would any of the stuff they post garner funding. Their top articles include such things as "The Beer Belly of America", "The Price of Weed", "Church vs. Beer? on Twitter" and "Church, bowling, guns and strip clubs."
They're doing this as a fun hobby, not serious academic research. There is no funding, no grants, nothing.