Nathan Robertson of Business2Community recently wrote, "Now that business owners are starting to take social media seriously, they are finding that understanding the information that is coming to them at lightning speed has a way of getting away from them before they can make any sense of it. This new form of big data means the creation of a new way of aggregating and breaking down data so businesses can understand what consumers and potential consumers are saying about them, who is buying from them, who isn’t—and why not."
He goes on, "Most people who are pleased with a product won’t take the time to write a review on Amazon, for example—but they may very well mention it to a friend or as a post in their newsfeed on Facebook or Twitter, or take the time to pin the product on Pinterest. These new forms of 'reviews' so to speak, tell companies what they otherwise might not ever know, and certainly would not have been privy to in decades past. But in order to make good use of these reviews and make decisions about everything from advertising to product design, big data from social media platforms must come to decision makers in an organized fashion."
Robertson continues, "How can we do this as business owners or managers, especially when people aren’t tagging the names of our companies or hashtagging us in their comments or tweets? We have to turn to a system that allows us to look into their world, and one of the most powerful systems that does this is called latent semantic analysis, or LSA. Oracle Social Engagement and other LSA systems use a cloud to monitor the 'language modeling' arrangement that understands both long and short tail keywords and their classification. Perhaps more importantly, LSA systems also pick up on the use of language that is not precisely the keywords a company may be looking for to see how they’re doing on social platforms."
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