Last Updated on by Kumar Raja

What Are The Applications Of Text Mining In Data Science?

The data analysis or exploration process in Data Science involves a sequence of steps & data mining is one among them. Now, Text Mining is one of the different techniques that is associated with Data Mining & it is all about extracting the textual data from varied sources. If you are intended to become a Data Scientist, then having an intense knowledge of the process involved in Text Mining is very crucial.

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In this blog post, let’s take a clear look at the various applications of Text Mining.

  • Risk Management

Text Mining has a crucial role to play in the risk analysis technique in Data Science. Data Scientists make use of advanced text mining tools like SAS Text Miner to analyze the ongoing market trends by analyzing the textual data collected from different social media sites, customer reviews across different platforms & this will help the stakeholders in making accurate decisions.

  • Customer Care Service

The rapid advancements in NLP has made the process of Text Mining to become very crucial for the enterprises to enhance their Customer Care Service. By analyzing the textual data that is collected from surveys, customer feedback, and customer calls, etc enterprises can easily understand & reach out to their customers grievances efficiently.

  • Fraud Detection

The application of Text Analytics is more prevalent in the Banking, Insurance & Finance sectors. By analyzing the large volumes of textual transactional data that is generated as a part of the day-to-day users activities, the financial enterprises can easily detect and prevent frauds.

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