Map Measures U.S. Mood on Twitter
Northeastern University computer scientist Alan Mislove claims to measure the "pulse of the nation." This quietly hypnotic infographic tracks the mood of Twitter users across the United States, conveying the information through a color- and shape-shifting map of the country. But how do they distinguish happy tweets from sad ones? I'll let New Scientist do the explaining:
To glean mood from the 140-character-long messages, the researchers analysed all public tweets posted between September 2006 and August 2009. They filtered them to find tweets that contain words included in a psychological word-rating system called Affective Norms for English Words – a low-scoring word on ANEW is considered negative, a high-scoring one positive. They also filtered out tweets from users outside the US, and also from those in the US who did not include their exact location – for example, their city – in their Twitter profile.
That left 300 million tweets, each of which was awarded a mood score based on the number of positive or negative words it contained. For example, "diamond", "love" and "paradise" indicate happiness, whereas "funeral", "rape" and "suicide" are negative. "Dentist" is fairly neutral.