Each of the social sciences (Anthropology, Economics, Political Science, Social Psychology, and Sociology) and related fields (Geography, History, Communication, Linguistics, Management Science) witnessed the introduction of computation into its own frontiers of theory and research within a few years. However, formal training in computation did not begin until decades later through high-level software packages for statistical applications (SPSS, SAS, Stata), followed by true programming languages (S and R), as well as computational applications to content analysis, network models, and social simulations.

Those were the origins of CSS, a fledging field that has evolved from pioneering roots that began with primitive algorithms running on archaic computers with (mostly) historical interest, to today’s object-oriented models running on modern and more powerful computers that would have seemed like science fiction even to Isaac Asimov’s psychohistorian Hari (“The Raven”) Seldon in Foundations. What about the future? The future of CSS will be written in the language of advanced distributed computing, graphic processing units (GPU), quantum computing, and other information technologies still at the frontiers of computational science.

Introduction to Human Behavioral Biology

This is a pre-introduction to set the scene of how human behavior changes and some critical thinking. Stanford professor Robert Sapolsky gave the opening lecture of the course entitled Human Behavioral Biology and explains the basic premise of the course and how he aims to avoid categorical thinking.
Human Behavioral Biology

Behavioral Evolution

Stanford professor Robert Sapolsky lectures on the biology of behavioral evolution and thoroughly discusses examples such as The Prisoner’s Dilemma.
Behavioral Evolution

Behavioral Evolution II

This two-part series on evolution focusing on individual and kin selection, behavioral logic, competitive infanticide, male/female animal hierarchies, sex-ratio fluctuation, intersexual competition, imprinted genes, sperm competition, inbred-founder populations, group and multi-level selection, and punctuated equilibrium.
Behavioral Evolution II

Choice, Dynamic Choice, and Behavioral Economics

Economist David Kreps argues that traditional economic models of “rational decision making” fail to capture the complexity of how real people make important choices.
David Kreps: Choice, Dynamic Choice, and Behavioral Economics


Dr. Wu received his Master’s degree in Neuroscience from Duke University and earned his Ph.D. in Neuroscience at Vanderbilt University, focusing on research into learning and memory. He then began a 20-year career in Neuroscience at the University of Minnesota. He built one of the first two local marketing firms that specialize in Search Engine Optimization, science-based website design and conversion optimization. Over the last 20 years, growing research from Neuroscience, Social Psychology and Behavioral Economics has been providing new insights on how the brain makes buying decisions. That gave birth to a new field, Neuromarketing.
Behavior Change Experiments


Professor Matthew Salganik of Princeton University gives an introduction to the interdisciplinary field of computational social science, which employs digital data sources and machine learning to study human behavior.
Introduction to Computational Social Science

Computational Social Science: Progress & Future Challenges

Duncan Watts and his talk on the progress and future challenges of computational social science. The concept of not just studying the change in society, but also the areas that did not change.
Progress & Future Challenges

Frontiers of Computational Social Science

Dr. Joshua Epstein is a pioneer of Agent_Based Modeling, in which artificial societies of software people interact on simulated landscapes to generate realistic social dynamics, from revolutions, to epidemics, to the reconstruction of ancient civilizations. As immersive movies, he ill show a fascinating array of agent-based models, ranging from a “toy” school playground up to the deadly serious 7 billion agent Global Epidemic Model, used during Ebola and earlier pandemics. He will discuss his plans to populate these models with Agent_Zero, his next-generation software person grounded in contemporary neuroscience, and endowed with emotions like fear. Epstein’ vision of large-scale spatial models populated by neuro-cognitive agents represents the frontier of computational social science.
Progress & Future Challenges

Summer Institute in Computational Social Science

The Summer Institute is co-organized by Christopher Bail and Matthew Salganik with the purpose to introduce graduate students, postdoctoral researchers, and beginning faculty to computational social science.

Summer Institute in Computational Social Science
Deep Learning for Causal Inference

The Role of Surveys and Big Data

In this video, Professor Matthew Salganik discusses combining surveys and big data for survey research. Link to slides: https://github.com/compsocialscience/
Introduction to Computational Social Science

Irresistible: The Rise of Addictive Technology and the Business of Keeping Us Hooked

Welcome to the age of behavioral addiction—an age in which half of the American population is addicted to at least one behavior. We obsess over our emails, Instagram likes, and Facebook feeds; we binge on TV episodes and YouTube videos; we work longer hours each year; and we spend an average of three hours each day using our smartphones. Half of us would rather suffer a broken bone than a broken phone, and Millennial kids spend so much time in front of screens that they struggle to interact with real, live humans.
Tracks the rise of behavioral addiction, and explains why so many of today’s products are irresistible. Though these miraculous products melt the miles that separate people across the globe, their extraordinary and sometimes damaging magnetism is no accident. The companies that design these products tweak them over time until they become almost impossible to resist.
By reverse engineering behavioral addiction, Alter explains how we can harness addictive products for the good—to improve how we communicate with each other, spend and save our money, and set boundaries between work and play—and how we can mitigate their most damaging effects on our well-being, and the health and happiness of our children.

We spend 4 hours a day on our phones