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Trendwatching in large quantities of social content

Photo courtesy of Tom Purves via Flickr

Photo courtesy of Tom Purves via Flickr

Managing huge quantities of data has become one of the central challenges of science today, according to two articles in the New York Times and the Economist recently. For example, the International Astronomical Union met in August and discussed astronomy’s “trend towards mining data gathered by computers rather than peering into telescopes.”

Their concern is that mired in the muck of billions of data points, astronomers will lose the big picture. In social media monitoring, the challenge is similar: how do you find the big ideas from people with valuable suggestions about your business amongst the thousands of less insightful mentions?

Honing your search terms is an important step. For users of the Cision Social Media Dashboard, we often remind communications professionals to search “point of need” terms.  That means try to think of words or phrases people might use at the time when they would need your product or service. One well-known example of this approach is the Google Flu Trends application, which predicts where flu outbreaks will occur based on where people are googling terms such as common flu symptoms or antibiotic medications.

Especially for consumer brands with large volumes of innocuous mentions, filtering out the important suggestions, compliments with substantive feedback and even informative criticisms can take some experimenting. But in terms of improving relationships and gaining insights, the payoff is well worth the effort.

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