Text Mining 101: A Stepwise Introduction to Topic Modeling using Latent Semantic Analysis (using Python)

Introduction

Have you ever been inside a well-maintained library? I’m always incredibly impressed with the way the librarians keep everything organized, by name, content, and other topics. But if you gave these librarians thousands of books and asked them to arrange each book on the basis of their genre, they will struggle to accomplish this task in a day, let alone an hour!

However, this won’t happen to you if these books came in a digital format, right? All the arrangement seems to happen in a matter of seconds, without requiring any manual effort. All hail Natural Language Processing (NLP).

Have a look at the below text snippet:

As you might gather from the highlighted text, there are three topics (or concepts) – Topic 1, Topic 2, and Topic 3. A good topic model will identify similar words and put them

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