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.'"

Comments

How about black-to-white racism?

[Anonymous Coward]

are they recording that or giving it a pass because life was unkind to the african americans 150 years ago?
Chris Rock will tell you himself. Some white people are racist but almost ALL black people are racist.

Re:How about black-to-white racism?

[kenh]

Silly logical thinker, haven't you heard, a black person can not, by definition, be racist.

So now we have proof

[Hentes]

that all Alabamians are dirty racists!

Re:Actually Measured

[Hatta]

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.

Doesn't matter, with an effect size this large you don't need that much precision. As bad as 'information scientists' may be at statistics, 'random guy on slashdot' is always worse.