CMSC 191: Computational Social Network Analysis
Mapping the Networked World
Embedded Files
This topic introduces the theoretical and computational foundations of Computational Social Network Analysis (CSNA). The discipline is described as the convergence of sociological inquiry and algorithmic design, where social relations are represented as graphs and studied through efficient computational methods. The handout explains how networks encode influence and diffusion processes, emphasizing that matrix algebra enables structural measurement and visualization.
Ethical responsibilities in handling large-scale relational data are highlighted, particularly concerning privacy, consent, and stewardship of public information. Finally, the universality of graph theory is presented, demonstrating how identical computational tools apply across social, biological, and technological systems. The topic establishes CSNA as both a science of structure and a practice of responsible data representation.
Learning Outcomes
Learning Outcomes
Explain the concept of networks as universal structures that characterize social, natural, and technological systems.
Recognize the ethical and privacy considerations involved in studying human connections computationally.
Appreciate the interdisciplinary motivation that unites computation, data, and social interpretation.
Guide Questions
Guide Questions
How is the idea of “connection” reframed as a measurable scientific construct?
In what ways can network thinking unify the study of natural and social systems?
Why must ethics and data stewardship be central in computational analysis?
How does network analysis redefine how human and collective behavior are understood?
Topic Outline
Topic Outline
Mapping the Networked World* (class handout)
Setting the Computational Stage
Course Overview and Expectations
The Nexus of Code and Society
Modeling Ties: Relationships as Data
From Matrix to Map: Encoding Social Structure
Research Ethics and Data Privacy
The Computational Challenge to Privacy
Public Data, Private Lives: The Stewardship Role
The Concept of “Networks Everywhere”
G(V, E) as a Universal Language
Transferable Insights: Algorithms Beyond the Social
From Structure to Universality
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The semester at a glance:
Mapping the Networked World
Validity and Reliability . . .
Project Development . . .
Implementation . . .
Reading List
Reading List
Barabási, Albert-László, and Réka Albert. "Emergence of scaling in random networks." Science 286, no. 5439 (1999): 509-512.
Granovetter, Mark S. "The strength of weak ties." American Journal of Sociology 78, no. 6 (1973): 1360-1380.
Wasserman, Stanley, and Katherine Faust. Social Network Analysis: Methods and Applications. Cambridge University Press, 1994. (Core Text)
Access Note: Published research articles and books are linked to their respective sources. Some materials are freely accessible within the University network or when logged in with official University credentials. Others will be provided to enrolled students through the class learning management system (LMS).
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