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An interesting link between human emotions and computing: data mining of social data
In 10 seconds? Statistics analysis does not work only on numbers. Many techniques can be applied to written texts, as blogs from social networks, to discover unknown relationship among data or to study human emotions.
Don't believe it? A corpus of 300000 Twitter texts has been analyzed by Alexander Pak and Patrick Paroubek (read more) and a "sentiment classifier" was built using statistical techniques.
Why the need of statistical techniques to study "human" concerns, such emotions or other social issues? In last years, the interest for social science questions, about welfare, education and many other fields, led to the collection of a huge amount of data, known as "big data".Data mining techniques allow the analysis of large amounts of data and are very helpful to discover the set of attributes that is useful for making behavioral predictions, to find unknown relationships among data, and more.more
How can data mining help in social data analysis?
Social scientists typically use machine-learning -, to measure a certain characteristic or latent quantity in the data (Justin Grimmer). For example. Scime and Murray (2007) data mined more than 900 attributes from the American National Election Studies data set to identify 13 measures that successfully predict for which party an individual will vote in a presidential election or whether that individual will vote at all. more.
With data mining, terrorism analysts- have associated a number of social, political, and economic conditions at the national level with the likelihood that a nation will fall victim to a terrorist event. One of these is the level of democracy. more
In education-,data mining was used to study the characteristics of successful scholarship recipients in a scholarship program.more