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Chris J. Vargo and Scott Bradley

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.

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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.

This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

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What's inside

Syllabus

Network Analysis Introduction and Terminology
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.
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Network Analysis Data Structures and Calculations
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.
Preparing and Visualizing Social Networks
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.
Preparing and Visualizing Semantic Networks
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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills and tools that are useful for personal growth and development
Teaches concepts and techniques that are highly relevant in an academic setting
Explores topics and techniques that are not well-known or easily accesible
Explores network analysis through unique perspectives and ideas
Explores concepts and techniques that are highly relevant industry
Provides hands-on labs and interactive material, making the learning process more engaging

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Network Analysis for Marketing Analytics with these activities:
Review Terminology
Prepare for network analysis by defining concepts.
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Show steps
  • Read course syllabus and skim first chapter of textbook
  • Find and read 2-3 articles on network analysis to gather background information
  • Complete any practice problems or exercises in the textbook
Find a Mentor in Network Analysis
Connect with an experienced professional for guidance and support.
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  • Identify potential mentors through professional networks or online platforms
  • Reach out to potential mentors and express your interest in their guidance
  • Schedule regular meetings or communications to discuss your progress and receive feedback
  • Follow up with your mentor and show appreciation for their support
Build a Resource Compilation
Consolidate and organize learning materials for easy reference.
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Show steps
  • Create a platform or document to store the resources
  • Search for and collect high-quality articles, datasets, videos, and other materials
  • Categorize and organize the resources
  • Add brief annotations or summaries for each resource
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Explore Python Libraries for Network Analysis
Enhance technical proficiency in Python for network analysis.
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Show steps
  • Identify Python libraries for network analysis, such as NetworkX or igraph
  • Find tutorials or documentation on these libraries
  • Follow the tutorials to understand the functionality of the libraries
  • Practice using the libraries by creating small scripts or programs
Attend a Network Analysis Workshop
Expand knowledge and skills through a hands-on workshop.
Browse courses on Network Analysis
Show steps
  • Find a workshop on network analysis that aligns with your interests
  • Register and attend the workshop
  • Actively participate in the activities and discussions
  • Network with other attendees
Visualize Networks
Practice and refine network visualization techniques.
Browse courses on Network Visualization
Show steps
  • Choose a dataset such as the Enron email dataset
  • Load the dataset into a programming environment
  • Plot the data using a visualization library such as Gephi or NetworkX
  • Identify and interpret patterns in the visualization
  • Document the process and observations
Discuss Case Studies
Engage with peers to apply network analysis to practical scenarios.
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  • Find a group of peers to collaborate with
  • Choose a case study relevant to network analysis and marketing
  • Analyze the case study using network analysis techniques
  • Discuss the findings and insights with the group
  • Prepare a summary of the discussion and key takeaways
Practice Data Visualizations
Visualizing relationships within a network will reinforce concepts of graph theory and network analysis.
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Show steps
  • Create a simple graph using a tool like Gephi or NetworkX.
  • Experiment with different visualization techniques, such as node-link diagrams or force-directed layouts.
  • Add attributes to nodes and edges to create more complex visualizations.
  • Interpret the visualizations to identify patterns and trends in the data.
Build a Network Model
Apply network analysis to a real-world problem.
Show steps
  • Identify a real-world problem or business challenge that can be addressed using network analysis
  • Collect or gather relevant data
  • Design and build a network model using a programming environment
  • Perform network analysis on the model
  • Interpret the results and make recommendations based on the analysis
Build a Social Media Network Analyzer Tool
Developing a tool to analyze social media networks will provide hands-on experience with network data and analysis techniques.
Browse courses on Network Analysis
Show steps
  • Choose a programming language and framework for your tool.
  • Design the architecture of the tool, including data structures and algorithms.
  • Implement the tool's functionality, such as data import, analysis, and visualization.
  • Test and debug the tool to ensure its accuracy and efficiency.

Career center

Learners who complete Network Analysis for Marketing Analytics will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use data to solve complex problems in a variety of fields, including marketing, finance, and healthcare. A Data Scientist may use network analysis to understand the relationships between different entities in a dataset, such as the relationships between customers, products, and transactions. This course provides an overview of network analysis and covers topics such as network data structures, calculations, and visualization. This knowledge can help Data Scientists gain insights into complex datasets and develop more effective solutions to problems in a variety of fields.
Data Analyst
Data Analysts use data to solve business problems. A Data Analyst may use network analysis to understand the relationships between different entities in a dataset, such as the relationships between customers, products, and transactions. This course provides an overview of network analysis and covers topics such as network data structures, calculations, and visualization. This knowledge can help Data Analysts gain insights into complex datasets and develop more effective solutions to business problems.
Business Analyst
Business Analysts use data to identify and solve business problems. A Business Analyst may use network analysis to understand the relationships between different business units, processes, and stakeholders. This course provides an overview of network analysis and covers topics such as network data structures, calculations, and visualization. This knowledge can help Business Analysts gain insights into complex business processes and develop more effective solutions to business problems.
Risk Analyst
Risk Analysts identify and assess risks to businesses and organizations. A Risk Analyst may use network analysis to understand the relationships between different risk factors, such as economic conditions, regulatory changes, and natural disasters. This course provides an overview of network analysis and covers topics such as network data structures, calculations, and visualization. This knowledge can help Risk Analysts gain insights into complex risk factors and develop more effective risk management strategies.
Market Researcher
Market Researchers study market trends, customer needs, and competitor activities. A Market Researcher may use network analysis to understand how ideas and information spread through a social network, or to analyze customer feedback on a product or service. This course provides an overview of network analysis as it pertains to marketing data, specifically text datasets and social networks. This knowledge can help Market Researchers gain insights into how people interact with each other and with different brands or products, which can be used to develop more effective marketing strategies.
Quantitative Analyst
Quantitative Analysts use data to develop and validate financial models. A Quantitative Analyst may use network analysis to understand the relationships between different financial instruments, such as stocks, bonds, and currencies. This course provides an overview of network analysis as it pertains to text datasets and social networks, which can be applied to financial data. This knowledge can help Quantitative Analysts develop more effective financial models that are more accurate and reliable.
Marketing Analyst
Marketing Analysts use data to analyze the effectiveness of marketing campaigns and identify opportunities for improvement. A Marketing Analyst may use network analysis to understand how ideas and information spread through a social network, or to analyze customer feedback on a product or service. This course provides an overview of network analysis as it pertains to marketing data, specifically text datasets and social networks. This knowledge can help Marketing Analysts gain insights into how people interact with each other and with different brands or products, which can be used to develop more effective marketing strategies.
Product Manager
Product Managers develop and execute product strategies for businesses. A Product Manager may use network analysis to understand the relationships between different products and features, and to identify opportunities to create a more cohesive and effective product strategy. This course provides an overview of network analysis as it pertains to text datasets and social networks, which can be applied to product data. This knowledge can help Product Managers develop more effective product strategies that engage with the target audience.
Public Relations Specialist
Public Relations Specialists manage the public image of businesses and organizations. A Public Relations Specialist may use network analysis to understand the relationships between different media outlets and journalists, and to identify opportunities to place positive stories about their organization. This course provides an overview of network analysis as it pertains to social networks, which can be applied to media data. This knowledge can help Public Relations Specialists develop more effective public relations strategies that engage with the target audience.
Brand Manager
Brand Managers develop and execute brand strategies for businesses. A Brand Manager may use network analysis to understand the relationships between different brands and products, and to identify opportunities to create a more cohesive and effective brand strategy. This course provides an overview of network analysis as it pertains to text datasets and social networks, which can be applied to brand data. This knowledge can help Brand Managers develop more effective brand strategies that engage with the target audience.
Social Media Analyst
Social Media Analysts use data to analyze the effectiveness of social media campaigns and identify opportunities for improvement. A Social Media Analyst may use network analysis to understand the relationships between different social media platforms, and to identify opportunities to improve the reach and engagement of their campaigns. This course provides an overview of network analysis as it pertains to social networks, which can be applied to social media data. This knowledge can help Social Media Analysts develop more effective social media campaigns that engage with the target audience.
Content Strategist
Content Strategists develop and execute content strategies for businesses. A Content Strategist may use network analysis to understand the relationships between different pieces of content, and to identify opportunities to create more effective content. This course provides an overview of network analysis as it pertains to text datasets, which can be applied to website content and other text-based data. This knowledge can help Content Strategists develop more effective content strategies that engage with the target audience.
Digital Marketing Manager
Digital Marketing Managers plan and execute digital marketing campaigns for businesses. A Digital Marketing Manager may use network analysis to understand the relationships between different digital marketing channels, and to identify opportunities to improve the effectiveness of their campaigns. This course provides an overview of network analysis as it pertains to social networks and text datasets, which can be applied to digital marketing data. This knowledge can help Digital Marketing Managers develop more effective digital marketing campaigns that engage with the target audience.
Social Media Manager
A Social Media Manager is responsible for planning, developing, and executing social media strategies for businesses. This course gives an overview of network analysis, which is a way to understand the relationships between different entities on a network. This knowledge can be applied to social media data to gain insights into how people interact with each other and with different brands or products. This course can help Social Media Managers develop more effective social media strategies that engage with the target audience.
Search Engine Optimizer
Search Engine Optimizers (SEOs) help businesses improve their visibility and ranking in search engine results pages (SERPs). An SEO may use network analysis to understand the relationships between different websites and web pages, and to identify opportunities to improve their website's ranking. This course provides an overview of network analysis as it pertains to text datasets, which can be applied to website content and other text-based data. This knowledge can help SEOs develop more effective strategies for improving their website's ranking in SERPs.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Network Analysis for Marketing Analytics.
Provides a comprehensive overview of social network analysis methods and their applications in various fields, including marketing. It valuable resource for students and researchers who want to learn more about the latest advances in network analysis.
Provides a comprehensive overview of data mining and analysis techniques, including network analysis. It valuable resource for students and researchers who want to learn more about the latest advances in data mining and analysis.
Provides a comprehensive overview of complex networks, including both theoretical and practical aspects. It valuable resource for students and researchers who want to learn more about the latest advances in complex networks.
Provides a comprehensive overview of statistical network analysis techniques using the R programming language. It valuable resource for students and researchers who want to learn more about the latest advances in statistical network analysis.
Provides a comprehensive overview of social network analysis techniques and their applications in various fields, including marketing. It valuable resource for students and researchers who want to learn more about the latest advances in social network analysis.
Provides a comprehensive overview of network analysis techniques and their applications in the social sciences. It valuable resource for students and researchers who want to learn more about the latest advances in network analysis.
Provides a comprehensive overview of social networks and their role in human society. It valuable resource for students and researchers who want to learn more about the latest advances in social network analysis.

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