Natural Language Processing in Public Perception Analysis – How deep can it go?

Natural Language Processing is a component of Artificial Intelligence (AI), through which machines understand and process human language as it is spoken or written. It helps to automatically perform repetitive tasks and thus provide useful data and insights. Natural Language Processing uses a technique called sentiment analysis (or opinion mining) to perceive the emotions in texts and thus helps to automatically analyze the public perception of brand on social media.

The overall public perception of the brand and where it stands regarding the opinions of the customers, can be easily evaluated through targeted sentiment analysis. NPL enables to go through the customer reviews of the brand mentioned and analyze the underlying emotions in it. The positive, negative, or neutral feedbacks presented by the customers are thus taken into consideration and in exchange provides an accurate analysis of the brand sentiment. Not only does it perceive the sentiment but also compares the data and shows exactly where the brand stands in the marketplace. The results are far more precise than any human analysis as machines are always subjected to their main concerns.

This fellow technique of NPL can acknowledge the brand’s crisis period and thus make it better before turning into anything serious. In addition, it helps the brand to detect the positive feedbacks and respond to them accordingly. Natural Language Processing is thus an indispensable tool in public perception analysis, it can go as deep as it is subjected to, and help brands to build their public image more effectively and effortlessly.