Hashtags as Big Data

Since they first appeared in 2007, hashtags have been a core part of Twitter’s success – they are a quick way to connect your content to others’ related content and, in doing so, hashtags help social media users participate in wider community conversations.   Previously seen as only the language of Twitter, Facebook and Google+ recently began to integrate hashtags into their platforms as well.  Although the move was initially interpreted as an attempt to cash in on the social advantages of hashtags, we also see these companies’ adoption of hashtags as an indication of their focus on “big data” analysis and advertising potential.    

Both Google+ and Facebook have crowed about the introduction of hashtags in their ability to deepen social engagement and conversation.  As Facebook’s product manager for hashtags, Greg Lindley, said,

“Hashtags are just the first step to help people more easily discover what others are saying about a specific topic and participate in public conversations.”

When Facebook first announced the addition of hashtags to the platform, the company was adamant in stating that hashtags were to be employed for the benefit of the Facebook user to more easily find relevant content. However, the public is not naïve to the monetization possibilities that accompany these symbols. Since Facebook first announced the addition of hashtags to their structure, speculation has swirled regarding their potential contribution to more streamlined targeting.

While it is true that many will enjoy using hashtags within these networks, it is hard to imagine search engineers behind the scenes aren’t keenly aware of the power that lies within manually-aggregated community content.   Are we to believe, as Facebook’s VP of Global Marketing Solutions, Caralyn Evans, insisted to Adage in a recent interview, that “…there’s no monetization plan for it [hashtags] right now”?   Whether there is a plan on the books or not, the implementation of hashtags clearly paves the way to analyze and reach those networks’ consumers in a new, “bigger” way.   Google+’s integration of hashtags clearly indicates this is their intent, at least.  Let me explain…

Google+, unlike Twitter and Facebook, automates hashtag markup.  Users don’t even have to remember to add the # symbol – they simply use a word or a phrase and G+ adds the # symbol to keywords it identifies as worthwhile.  This is the particular element that intrigues me – for Google to automate the markup, they are necessarily relying on a bigger data source.  Automated application of big data trends to content as it’s published creates… wait for it… bigger big data!   (Topic for another day: doesn’t this create an “information bubble” where certain trends are artificially reinforced?)  Google’s hashtag automation shows that at least they know hashtags are the same as “big data”.

Aggregating similar content deepens Facebook and Google’s reach into big data.  Hashtags are, by their very nature, harnessing the potential of people’s thoughts and interests and turning them into mineable information.   As it is still unclear exactly what the marriage of hashtags and advertising on both sites will look like, it’s evident that both Facebook and Google will benefit from a big data standpoint as hashtags continue to evolve into a major factor within this narrative.

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