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One of the questions i often get is what other applications can emerge from using Text Analytics and Data Mining. With Text Analytics and Data Mining we can find behavior patterns on many levels and -assuming that information such as Tweets will keep coming- the understanding of consumers can go to the next -and sometimes more personal- level.
One of these applications is Event Detection. I am not aware if Event Detection is provided by any tool at the moment but i believe that this type of analysis could become a next major source of consumer insights. But what exactly is “Event Detection”?
Since we are able to have a computer automatically identify whether a phrase contains positive, negative or neutral sentiment, perhaps we could use Text Analytics and Machine Learning to detect that a specific event has occurred to an individual from the Tweets that someone posted such as “i’ve just returned from holidays”. But that’s not all. We can mine for patterns of consumer behavior given the fact that an event has occurred. And that potential knowledge from such an analysis could be very powerful. Because apart from the emotions that a product / service / person generates, the same applies for events happening in our lives. These events and the emotions they create can sometimes change our lives and also drive our decisions. A logical next step is to collect several behavioral Data and use Data Mining to analyze this information.
I will discuss an example of using Event Detection towards the end of my presentation on the 7th Annual Text Analytics Summit in Boston this May along with the reasons for such an analysis being important and i am looking forward to the reactions.