Computational Social Science

With the rapid increase in the availability and use of computers, and their capacity to process information rapidly, the value of knowledge associated with computational resources has increased substantially. The purpose of this area is to encourage students to learn a set of methods that are associated with various computational orientations to social science. This includes such things as social network analysis, social sequence analysis, topic modeling, and other “Big Data” approaches to data analysis. This is largely a methods-oriented area, but it also addresses emerging theories about sampling and the nature of social relationships within a highly networked society.

Related people

Image of Michael Macy
Michael Macy

Distinguished Professor of Arts and Sciences in Sociology, Director of the Social Dynamics Laboratory

Image of Cristobal Young
Cristobal Young

Associate Professor

All research areas

Community and Urban Sociology    Computational Social Science    Culture    Economy and Society    Gender    Inequality and Social Stratification    Methodology    Organizations, Work and Occupations    Policy Analysis    Political Sociology and Social Movements    Race, Ethnicity and Immigration    Science, Technology and Medicine    Social Demography    Social Networks    Social Psychology    Sociology of Education    Sociology of Family    Sociology of Health and Illness   
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