Sentiment Analysis with Natural Language Processing

Sentiment Analysis with Natural Language Processing

February 6, 2019 DATAcated Challenge 0

There are many business applications for Natural Language Processing but one that I feel it instrumental to success is Sentiment Analysis.

We perform sentiment analysis all the time and we may not even realize it. For example if you were to go to Amazon and search for an item (say…The Disruptors:Data Science Leaders book) usually the first thing you look at is the ratings. You analyze the sentiment¬†of what people think of the item. If it is 4 or above stars, then you would say that is a positive sentiment. If it is 3 stars, then that is neutral and if it is 1 or 2 stars you would say those are negative.

Sentiment analysis is just classifying those reviews as positive, neutral or negative automatically based on the content.

Say you are a business and you have just released a new product. You will want to gauge the sentiment of your users and that new product. What are they saying about the product?  Is it generally positive? By using Natural Language Processing, you can process this content from blogs, social media, Reddit, etc. in near-time to see what the overall sentiment is. From there you can look at what people like or dislike.

As you can see, this is a powerful tool to provide insights that can help shape your overall business strategy and help focus on product improvements directly based on this sentiment.

By: Sean Grant


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