A machine algorithm that can detect sarcasm? I know what you’re thinking…”That’s the most useful thing I have ever heard of!” (yuk, yuk, yuk). Believe it or not, it’s true. In a recent article, Popular Science reported that an Israeli research team has developed just such an algorithm that performs with 77% accuracy.
Besides bringing us one step closer to creating machines that will one day conquer and replace humanity, jokes and all, is such an algorithm really all that practical?
It could be.
It’s a good idea and common practice for many e-commerce sites to respond to any negative customer reviews they receive in order to keep individuals satisfied with their products or services. Not only does this give businesses a chance to rectify any issues their customers may have encountered, but it also allows people to see the quality of customer service and care provided. However, issues can arise for larger e-commerce sites. An e-commerce site that consists of many products and receives a great number of reviews may not always be able to respond to negative comments in a timely manner.
If starred reviews are part of your site’s review process, you might be able to just sort out the negative reviews in an easy manner, but this isn’t always fool-proof. Some customers have a tendency to pass right by the starring process and go straight for the comments. This is where the sarcasm algorithm could potentially come into play in helping you identify reviews that are less than glowing.
I’m not saying using such an algorithm would be the end all to sorting out the necessary reviews to respond to, but it could be part of the solution. The algorithm could be integrated with review systems and run as a secondary detection process, allowing sites to find sarcastic reviews and respond appropriately if need be.
Trust me. I’m not trying to take all the fun out of online product reviews. I love a good Three Wolf t-shirt review just as much as the next guy, but think of how much this sarcasm algorithm could help businesses with engaging customers; businesses are faced with engaging people before, during and after the purchase process.
Let me know your thoughts on this new algorithm. And although it’s tempting…please leave the sarcasm out of your comments on this one.