Using data to drive business intelligence

Whilst it’s tempting to think of social data as largely frivolous, it is increasingly evident that it is capable of revealing a great deal about us, both collectively and individually.

For instance, a Penn State study found that they could use Twitter data to predict the likelihood that someone would enrol on Obamacare, whilst another trawled social media to predict when someone might be tempted to join IS.

This kind of behavioral analysis has been available after Twitter opened up its data pipe to researchers via projects such as Gnip, which is an open source repository for social data.

Predictive analytics in finance

This kind of predictive analytics is also evident in finance, with the New York Stock Exchange teaming up with Social Market Analytics (SMA) a few years ago to test whether sentiment analysis could predict share movement.

This availability of data coincides with our greater understanding of behavior. For instance, we know that fund managers tend to invest more in companies that are based near them, or where they are connected to employees via their old school tie.

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