The Analytics Executive Email List Vidhya

Trends between yoga keywords modified with the word “beginner” versus those that are modified with the word “advanced”. This will give me more clues about what Google thinks is executive email list important to searchers looking for those types of terms, and how I might be able to better optimize for those terms. If you want to run this kind of analysis for your SERP data, follow this simple walkthrough by Kaggle based on applying PoS tagging to movie titles. It walks executive email list you through the process I’ve gone through to create the visuals used in the screenshots above. Topic Modeling Based on SERP Data.

Topic modeling is another really useful technique that can be deployed for our SERP analysis. What it refers to is a process of extracting topics hidden in a corpus of text; in our executive email list case the SERPs, for our set of target keywords. While there are a number of different techniques for topic modeling, the one that seems favored by data scientists is LDA (Latent Dirichlet Allocation), so that is the one I chose to work executive email list with. A great explanation of how LDA for topic modeling works comes from the Analytics Vidhya blog: “LDA assumes documents are produced from a mixture of topics.

Those topics then generate words based on their probability distribution. Given a dataset of documents, LDA backtracks and tries to figure out what topics would create those executive email list documents in the first place.” Although our keywords are all about ‘yoga’, the LDA mechanism we use assumes that within that corpus there will be a set of other topics. We can also use the Jupyter Notebook interface to create interactive visuals of these topics executive email list and the “keywords” they are built from. The reason that topic modeling from our SERP corpus can be so valuable to an SEO, content marketer or digital marketer is that the topics are being.