• Specialization: Text Marketing Analytics
  • Instructor: Vargo,Chris
  • Prior knowledge needed: None

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Learning Outcomes 

  • Describe the concept of network analysis and related terminology
  • Apply network analysis to marketing data via a peer-graded project
  • Visualize a network based on centrality and other statistics via homework
  • Extract marketing insights from a network via a peer-graded project

Course Content

Duration: 2h

In this module, we will learn the key concepts in network analysis and the key terminology, including semantic and social networks. We will also survey common network analyses in marketing. 

Duration: 1h

In this module, we will learn how networks are prepared and the common data formats that represent networks. We will learn the differences between different network calculations and how networks are presented visually.

Duration: 4h

In this module, we will learn how to parse tweet JSON, extract mentions and text, load connections into edge lists, and visualize the network in Google Colab.

Duration: 4h

In this module, we will learn how to parse tweet JSON, process text into features, load connections into edge lists, and visualize the network in Google Colab.

Duration: 1.25h

You will complete a peer reviewed project worth 20% of your grade. You must attempt the final in order to earn a grade in the course. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.

Note: This page is periodically updated. Course information on the Coursera platform supersedes the information on this page. Click View on Coursera button above for the most up-to-date information.