INAUndergraduate courses
Introduction to Network Analysis
A mix of quantitative and qualitative methods for describing, measuring and analyzing social networks — who is influential, and how things spread.
- Introductory
- 4 weeks
- Approx. 15 hours per week
- 3 semester hours
About this course
This course teaches a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks. You learn how to identify the influential people in a network, how to follow the propagation of information through one, and how to apply those techniques to real problems — the sort of understanding a manager needs of the social environment their organization sits in or has built.
Who this course is for
Marketing and IT managers, people who work in organizations with a social media presence they want to manage and analyze, and people in organizations that have — or plan to have — their own social networks and want to understand the environment they are creating.
What you will learn
6 outcomes
By the end of this course, you will be able to:
- Visualize networks of connections among entities or people
- Measure attributes of networks
- Measure attributes of users and of the ties among them
- Sample from networks that would be too large to analyze as a whole
- Generate and study hypotheses about networks
- Analyze the propagation of things through networks
Week by week
4-Week curriculum overview
This curriculum is identical across all start dates. Expand a week to explore the topics covered.
- Weeks
- 4
- Your week
- Approx. 15 hours
- Level
- Introductory
Network analysis basicsWeek 1
- Basic terminology
- Metrics
- Visualization
The social networkWeek 2
- Tie strength
- Trust — user attributes and behavior
AnalyticsWeek 3
- Modeling
- Sampling
- Content analysis
- Propagation
ApplicationsWeek 4
- Location
- Filtering and recommender systems
- Business use
Instructors
Expert-Led Guidance
Each cohort is led by dedicated instructors and assistant teachers who actively lead weekly discussions, provide personalized feedback and grade your assignments.
Dr. Jennifer Golbeck
Dr. Jennifer Golbeck is an Associate Professor in the College of Information Studies at the University of Maryland, College Park. Her research focuses on analyzing and computing with social media: building models of social relationships, particularly trust, as well as user preferences and attributes, and using the results to design and build systems that improve the way people interact with information online. She is a Research Fellow of the Web Science Research Initiative and was named one of IEEE Intelligent Systems' Top Ten to Watch in 2006. BS in Computer Science and BA in Economics (University of Chicago), MS in Computer Science (University of Chicago) and PhD in Computer Science (University of Maryland). Author of Analyzing the Social Web (2013), Trust on the World Wide Web: A Survey (2008) and Art Theory for Web Design (2005).
Before you start
What you need to know first
None. No particular background is required: computer scientists and people from a humanities background are equally able to do the work.
Course Format & Schedule
This is a 4-week, 100% online, asynchronous course.
- No mandatory live sessions: Log in and complete your work at times that fit your schedule.
- Weekly Releases: At the start of each week, you will receive new lecture materials and answer keys for the previous week's exercises.
- Interactive Community: Work through exercises, submit assignments, and engage with your instructor and peers via a private discussion board.
Homework
Assigned readings from the text, supplemental video lectures and further online readings, with weekly exercises you submit for individual feedback.
Texts
The required text for this course is Analyzing the Social Web by Jennifer Golbeck. Also available at Amazon here.
Software
This is a hands-on course. The required software is Gephi. The network analysis and visualization work is done in Gephi, which is open source and free to download.
Course dates
2026
11/02/2026to12/02/2026
Instructors: Dr. Jennifer Golbeck
12/07/2026to01/04/2027
Instructors: Dr. Jennifer Golbeck
10/05/2026to11/05/2026
Instructors: Dr. Jennifer Golbeck
Enrollment closed
Refund policy
Refund: $550 before start, $325 until day 7, none after. Date changes: first one free, then $25 each, until day 7. Full terms
FAQ
Do I need to be able to program?This course
No. The tools used are point-and-click, and there is no programming background assumed anywhere in the course. What you need is the willingness to work through the exercises on real network data.
Is this only about social media networks?This course
No. Social networks are where most of the examples come from, because that is where the data is easiest to get hold of, but the measures — centrality, tie strength, sampling, propagation — apply to any network of connected entities, including ones inside an organization.
Is there a money-back or satisfaction guarantee?Every course
Before your course starts, you get back what you paid minus a $100 processing fee. After it starts, until the deadline, which is the end of day 7 after the start date (for some courses, the end of the 10th of the month the course starts instead), you get back 50% of what you paid. After the deadline there is no refund. To ask, use the withdrawal form in your account or email support@learnstatistics.org. A person reviews every request.
Can I transfer to a later start date or withdraw after the course begins?Every course
Yes. You can move to another start date of the same course yourself, from My learning, until its move deadline (by default the end of day 7 after the start date). The first move of each course is free, and each later one costs $25. Withdrawing follows the refund rules above: 50% of what you paid until the deadline, and no refund after it. Moving does not restart the refund deadline: it is based on the earlier of the date you first bought and your new date.
How do I ask for a refund, and how long does it take?Every course
Use the withdrawal form in your account, or email support@learnstatistics.org. A person reviews every request: we reply within 2 business days and confirm the outcome within 5. Approved refunds go back to the card you paid with and usually arrive within 5 to 10 business days. The course then leaves your account and your classroom.
What if the course is cancelled?Every course
If we cancel your session, you choose: a full refund with no processing fee, or a free move to the next available date. The $25 fee for moving dates yourself is never refunded.
Who teaches the course?Every course
Each cohort is led by dedicated instructors and assistant teachers who actively lead weekly discussions, provide personalized feedback and grade your assignments. The instructor for each start date is listed on the course page.
Something not answered here? Ask us before you book — and the terms set out what a purchase covers.
Credit, and where it counts
This course carries a verified figure of 3 semester hours. A credit recommendation from the American Council on Education says what a course is worth; the institution receiving it decides whether to award it.
Anyone can take this subject: there is no application, and you do not have to be studying at a university. It also counts toward a degree at Thomas Edison State University in Trenton, New Jersey, which decides what to award for it. The course is taught online, so you take it the same way in New Jersey or anywhere else. The full position — including the limits each university publishes is on its own page, and worth reading before you buy.