Where do all the bigots live? In the US, at least, hatred for others seems to be concentrated more in the east than in the west - at least, as far as Twitter is concerned. Geography students at Humboldt State University in California have created a map of bigoted tweets south of the border.
The researchers analysed over 150,000 tweets that were geocoded with location data. They were looking for negative uses of keywords, such as 'fag', 'queer', 'gook', 'nigger', and 'wetback'.
They matched the tweets, using colours to indicate the number of hateful tweets compared to the average across the entire space. On the resulting map, light blue indicates some hate (more than the national average), whereas a bright, angry red shows the most hate. A lack of colour indicates a lower proportion of negative tweets relative to the national average.
What the map shows is that, whether they are homophobic, racist, or ableist (prejudiced against people with disabilities), most bigots with Twitter accounts seem to be located east of Colorado.
The researchers do a pretty good job of answering the inevitable questions about the survey. For example, students manually read each tweet to make sure that words were not being used in a positive way (many words, such as 'queer' and 'nigger' have been reclaimed by minority communities). Neither does the map simply reflect a denser population in the eastern US. it is normalised based on Twitter activity. As the researchers point out, vast numbers of people live in California, and yet there are relatively few bigoted tweets there (and I'm betting that there are far more tweeters in California than in New Mexico, which seems to be a hotbed for homophobic online users).
Facebook seems to do a pretty good job of removing hate speech where necessary, but Twitter has become a hotbed of hate and terrorism speech, according to a recent report by the Simon Weisenthal Centre. A lot of the time, social media analytics is used by companies to work out how online marketing campaigns are effecting customer buying patterns and sentiments. But this is one of the first times where we have seen similar techniques applied to measure levels of backwardness among a population.
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