Step by step guide to extract insights from free text (unstructured data)
Text Mining is one of the most complex analysis in the industry of analytics. The reason for this is that, while doing text mining, we deal with unstructured data. We do not have clearly defined observation and variables (rows and columns). Hence, for doing any kind of analytics, you need to first convert this unstructured data into a structured dataset and then proceed with normal modelling framework. The additional step of converting an unstructured data into a structured format is facilitated by a Word dictionary. You need a dictionary to do any kind of information extraction. Dictionary to do a sentiment analysis is easily available on web world. But, for some specific analysis you need to create a dictionary of your own.
This series of article starts from the very basic level to enable anyone, who might not have ever worked on text mining, be able to do one after a read. We will consider a business case to explain this framework and the practical usage. In this article we will start with an