Following on the heels of my post last week about the Google acquisition of MetaWeb, my favorite start-up Ellerdale announced that they’ve been acquired by Flipboard. As a reminder:

Ellerdale, founded in 2008, has developed a Web Intelligence technology that applies semantic analysis to large, real-time data streams to extract relevant and valuable information. To date, Ellerdale has indexed over 6 billion messages from around the social Web and currently processes nearly 70 million messages per day.

That’s right 6 BILLION messages at a growing rate of 70 million messages per day. One of the reasons I loved Ellerdale was that they were able to take virtually every bit of publically available social data and distill its context and meaning.They also had everything indexed and available for ad hoc search on demand (among many other cool things I won’t go into here). According to the press release, Ellerdale was acquired by Flipboard to make their social media magazine more relevant to readers:

“Ellerdale has developed an impressive solution for understanding the ever-increasing stream of social data coming at us every day… This technology will add deep relevancy for our readers… by always surfacing the most important and personally interesting information from Facebook, Twitter and other social networks.”

Pay VERY close attention here —> Ellerdale was acquired by a company that wants to make sense of Social Media for their niche application. How many companies do you think are building, or will be purchasing, applications that try to do something meaningful with social media data? If you answered a “gazillion”, I’d say you’re on the right track…

Any application that tries to do anything with raw text (social media) needs to be able analyze it and extract things like context, meaning, sentiment, and intent. Ellerdale provided a critical component of the foundation required to do these things. This is something most companies won’t want to take in-house because it’s a specialized art and science that falls outside their core competence; and it ain’t cheap to build something that processes and stores 3.5 million text records an hour. So the opportunity for a few independent players to step in here with their own analysis and open platforms  is, well, Mega

 

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