In the last few years, the explosion of user-generated content in social media (networks, forums, communities, etc.) has significantly increased the need to extract information from unstructured content. Oddly enough, text analytics superheroes, wondrous as their achievements are, are just average guys who figured out what they could do with the right technology.
Getting meaningful insights from natural language is no easy task. Text analytics value and accuracy grow as we add different layers of resources to the procedure. We explain how text analytics is like a multi-tiered wedding cake.
Before setting out on a quest to discover customer expectations, preferences, and aversions, you must know your allies, enemies, and weapons.
But, be on guard, since dangers lurk in the horizon…
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