{"id":51875,"date":"2021-12-06T17:44:55","date_gmt":"2021-12-06T12:14:55","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/we-used-natural-language-processing-techniques-to-analyze-the-reviews\/"},"modified":"2024-09-03T08:40:44","modified_gmt":"2024-09-03T03:10:44","slug":"we-used-natural-language-processing-techniques-to-analyze-the-reviews","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/we-used-natural-language-processing-techniques-to-analyze-the-reviews\/","title":{"rendered":"We used Natural Language Processing techniques to analyze the reviews online - Abhisek Srichandan, PGP AIML"},"content":{"rendered":"
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I am Abhisek Srichandan, and I have around one year of experience working as an Associate IT Consultant in a reputed organization. Before joining Great Learning's PGP Artificial Intelligence and Machine Learning Course<\/a>, I was in my final year of graduation then.<\/p>\n\n\n\n

Our company releases new food products every few years. Once it got released into the market, people started giving reviews. We had a lot of text data that we had in our hands.<\/p>\n\n\n\n

We had to find out the sentiment associated with the product. As the reviews increased, we had to find which products received more appreciation amongst people and which received negative reviews so that we could work on it.<\/p>\n\n\n\n

Without proper models and techniques to automate, it would have taken a lot of manual work.<\/p>\n\n\n\n

We used Natural Language Processing(NLP) techniques and used the Natural Language Toolkit to analyze the reviews online. We used web scraping techniques to pull in the reviews from different platforms and websites and worked on it.<\/p>\n\n\n\n

Later we found out the items that were receiving negative reviews. Reported the insights to the managers. As a solution, we used python libraries to find out the solutions. Reported the insights to the managers, who then focused on the specified items to do a Root Cause Analysis and modify the products accordingly.<\/p>\n\n\n\n

It helped save the organization's name and brand by rapidly identifying which products were doing bad and modifying or scrapping some products entirely so that the company didn\u2019t face losses. This helps me in spreading the good work, and the course gets more recognition in the industry, which I am already doing.<\/p>\n","protected":false},"excerpt":{"rendered":"

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