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How MarketMuse Determines Related Topics

Enter a topic into MarketMuse, and our proprietary patented technology creates a topic model by analyzing thousands of pages of content. Our method consists of an ensemble of algorithms that include phrase extraction (comprising a Bayesian statistical ensemble), graph analyses, and natural language processing.

Most importantly, by analyzing this vast amount of data, MarketMuse provides everything needed to create expert-level content. It’s not the copycat type of content that you get when only looking at the top 20.

Topics are determined based on semantic relevancy (their meaning), independent of how often they occur. They’re displayed based on relevance, with the most relevant appearing first.

The topic model created by any MarketMuse application consists of 50 topics semantically related to the main (focus) topic.

content strategy simple topic model

The topic model created for a Content Brief is far more sophisticated, consisting of:

  1. A topic model for the focus topic (the main subject of the content).
  2. A topic model for each section of content.
topic model comparison

Keep this in mind when comparing Optimize versus Content Brief.

Suggested Reading, A Technical Explanation of How MarketMuse Determines Related Topics.

Updated on July 14, 2021

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