Federico Pascual explains aspect-based sentiment analysis and then shows how to implement it with MonkeyLearn:
Imagine you have a large dataset of customer feedback from different sources such as NPS, satisfaction surveys, social media, and online reviews. Some positive, some negative and others that contain mixed feelings. You’d use sentiment analysis to classify the polarity of each text, right? After all, it’s already proven to be a highly efficient tool.
But, what if you wanted to pick customer feedback apart, hone in on the details, get down to the nitty-gritty of each review for a more accurate analysis of your customers’ opinions?
Cue aspect-based sentiment analysis (ABSA). A text analysis technique that breaks down text into aspects (attributes or components of a product or service) and allocates each one a sentiment level. This technique can help businesses become customer-centric, which means putting their customers at the heart of everything they do. It’s about listening to their customers, understanding their voice, analyzing their feedback and learning more about customer experiences, as well as their expectations for products or services.
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