A fundamental problem with this strategy is that is may bias the results towards prolific haters—i.e. people who are frequently hateful on Twitter. These people

A fundamental problem with this strategy is that is may bias the results towards prolific haters—i.e. people who are frequently hateful on Twitter. These people may live in places where social norms permit online hateful speech without repercussions. This strategy will miss people who are haters, but must be more subdued in their expressions of hatred online. It would be interesting to identify people who have posted just a few hateful messages—perhaps few enough that they can get away with it in their local social context. This may more sensitive to occult haters. Something like this: 1. Identify individual twitter users as being hateful in a particular category. For instance, user A uses the word "chink" 3x and "fag" 5x in 100 tweets, so he gets added to the "chink" and "fag" categories. Play with these threshold to see what makes sense. 2. Divide the # of hateful users in each category by the total # of users in that location. Allocation of users to location can be done proportional to the # of tweets they make from each location. Cool project :).