Complex network analysis is the quantitative study of interconnected systems that influence every aspect of our lives — from where we get our news and who we share ideas with, to how we travel and the people we interact with, to the products we purchase and the foods we eat. Northeastern University’s Master of Science in Complex Network Analysis equips students with the conceptual and analytical tools needed to find and analyze patterns of connections in networked systems and apply these techniques to solve real-world problems.
Program Details
Duration: 24 months
34-38 credit degree program
F1 Compliant Program
Admissions Deadlines
○ August 1, 2025 (domestic)
○ July 1, 2025 (international)
Interdisciplinary Training
○ Four concentration areas
Research/Professional Focus
- Fundamentals of Complex Networks
- Analyzing Complex Network Data
- Advanced Tools for Complex Network Analysis
- Visualizing Complex Networks
- Communicating Network Data
- Complex Social Systems
- Economic and Technological Networks
- Population Health Dynamics
- Complex Biological Networks
- Industry co-op internships
- Research lab rotations
- 2-credit "mastery" courses
- Thesis optional
Required Foundations Core (16 credits)
CNET 5050 | Fundamentals of Complex Networks (4 credits)
CNET 5051 | Analyzing Complex Network Data (4 credits)
CNET 5052 | Advanced Tools for Complex Network Analysis (4 credits)
CNET 5901 | Visualizing Complex Networks (2 credits)
CNET 5902 | Communicating Network Data (2 credits)
Concentration Core (10-12 credits)
Population Health Dynamics Concentration +
Students will build a strong foundation in complex network analysis, supplemented by coursework in biostatistics and epidemiology, including network modeling of infectious diseases and population health informatics. These skills are especially valuable for practitioners in public health agencies or for those modeling emerging epidemics in industry (e.g., insurance companies, and NGOs).
As a population health dynamics student, you’ll dive into biostatistics, epidemiology, networking modeling of infectious diseases, and population health informatics to help combat future outbreaks.}
Gain a foundation in network analysis, including coursework in biostatistics, epidemiology, network modeling of infectious diseases, and health informatics.
Complete 6–8 semester hours from the following:
BINF 6308 | Bioinformatics Computational Methods 1
NETS 5126 | Spreading on Networks: From Epidemics to Memes
NETS 5515 | Complex Network Analysis for Biological Systems
PHTH 5210 | Biostatistics in Public Health
PHTH 6440 | Advanced Methods in Biostatistics
Complex Social Systems Concentration +
Students will build a strong foundation in complex network analysis, supplemented by coursework in urban data analytics, digital trace data analysis, collective and cooperative behavior, or computational statistics. These skills offer students a competitive advantage in the ever-evolving landscape of social data in today's tech and scientific industries.
In the complex social systems concentration, you’ll hone your skills in urban data analytics, digital trace data analysis, collective and cooperative behavior, and computational statistics to analyze a range of social systems, including online social networks.}
Complete 6–8 semester hours from the following:
INSH 5304 | Social Network Analysis
INSH 6304 | Modeling and Analyzing Social Networks
NETS 5311 | Physical and Digital Human Traces
NETS 5314 | Complexity in Social Systems
NETS 5360 | Research Design for Social Networks
PPUA 5262 | Big Data for Cities
Economic and Technological Networks Concentration +
Students will build a strong foundation in complex network analysis, supplemented by domain-specific coursework in financial and economic networks. This may include topics ranging from econometrics to deep learning. This broad concentration is designed to give students targeted skill sets that will ultimately lead to real insights in business and finance.
Through the economic and technological networks concentration, you’ll be able to understand and predict market trends, risks, and opportunities through coursework on financial and economic trends, econometrics, and machine learning.
Understand and predict market trends, risks, and opportunities through coursework on financial and economic trends, econometrics, and machine learning.
Complete 6–8 semester hours from the following:
CS 7150 | Deep Learning
DS 5220 | Supervised Machine Learning and Learning Theory
DS 5230 | Unsupervised Machine Learning and Data Mining
MISM 6212 | Data Mining and Machine Learning for Business
NETS 5411 | Financial and Economic Networks
Complex Biological Networks Concentration +
Develop your skills in urban data analytics, digital trace data analysis, collective and cooperative behavior, and computational statistics to analyze a range of social systems, including online social networks
In the complex biological networks concentration, you’ll supplement your core network analysis skillset with coursework in bioinformatics, computational biology, and network medicine, studying biological systems at multiple scales, from gene regulation and protein interactions to ecological networks.}
Build a knowledge base around a range of topics in biomedical research, biotech, and emerging industries like network medicine and personalized therapeutics.
Complete 6–8 semester hours from the following:
Interdisciplinary Concentration Mastery (4 credits)
CNET 6061 | Analyzing Higher Order Networks (2 credits)
CNET 6063 | Probabilistic Mathematics of Networks (2 credits)
CNET 6099 | Special Topics in Complex Networks (2 credits)
CNET **** | Core course from different concentration (4 credits)
Experiential Courses: Select 2 courses (4 credits)
Select 2 courses:
CNET 6107 | Complex Network Analysis Research Rotation (2 credits)
CNET 6108 | Complex Network Analysis Capstone (2 credits)
CNET 6990 | Complex Network Analysis Thesis (2 credits)
(Optional) Professional/Research Co-op
CNET 6000 | Professional Development for Co-op (1 credits)
CNET 6964 | Complex Network Analysis Co-op (0 credits)
