Enterprise Communications


Social Media Analytics: Big Data, Big Voices, and Big Brother?

by Michael Brandenburg 15 Feb 2013
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In my research around the convergence of social media and Big Data techniques that defines social media analytics, I initially deemed this notion of social media data mining both “amazing and frightening”.

The amount and types of actionable information that could be divined from social media are actually quite staggering and can serve more than just enterprise marketing or social media departments. Actionable information can work its way throughout the organization to provide real value. However, the prospect of Big Data turning into Big Brother was a lingering thought throughout my conversations with certain vendors that are at the cutting edge of this new business intelligence opportunity.

My nagging feeling that we are being watched on social media actually went away for two reasons. First and foremost, those that I spoke with who are involved in this nascent market are highly cognizant of the very thin line between insightful and creepy, and take it as a responsibility to maintain that line.

The second reason, as it turns out, has more to do with my own perceptions of social media. It is easy to forget that when posting to Twitter or a public blog, we are broadcasting our sentiment - the Internet equivalent of shouting your message through a bullhorn in the town square. While other forms of electronic communication, like email, represent whispers to a small audience, social media is meant for shouting and sharing information.

In that sense, social media analytics is ultimately an automated way for organizations to listen and filter through all of the shouting. Given the public context of social media, the onus is not on organizations to decide whether they should listen. Rather, the onus is on users to decide whether they truly want their voice to be heard.

(Read more about social media data mining here: "Big Data and Social Media: The Perfect Storm")

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