Network analysis is a long-standing methodology used to understand the relationships between words and actors in the broader networks in which they exist. This course covers network analysis as it pertains to marketing data, specifically text datasets and social networks. Learners walk through a conceptual overview of network analysis and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project.
Network Analysis for Marketing Analytics
Network Analysis for Marketing Analytics
This course is part of Text Marketing Analytics Specialization
Instructors: Chris J. Vargo
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
10 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Build toward a degree
What you'll learn
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
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
3 assignments
Taught in English
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This course is part of the Text Marketing Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
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.
What's included
2 videos3 readings1 discussion prompt
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.
What's included
2 videos1 reading1 assignment
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.
What's included
1 video2 readings1 assignment1 programming assignment
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.
What's included
1 video2 readings1 assignment1 programming assignment
Offered by
Explore more from Data Analysis
University of Colorado Boulder
University of Virginia
Johns Hopkins University
University of Colorado Boulder
Build toward a degree
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
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