Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions. It involves the understanding of social agents, the interaction among these agents, and the effect of these interactions on the social aggregate. Although the subject matter and methodologies in social science differ from those in natural science or computer science, several of the approaches used in contemporary social simulation originated from fields such as physics and artificial intelligence. Some of the approaches that originated in this field have been imported into the natural sciences, such as measures of network centrality from the fields of social network analysis and network science. In relevant literature, computational sociology is often related to the study of social complexity. Social complexity concepts such as complex systems, non-linear interconnection among macro and micro process, and emergence, have entered the vocabulary of computational sociology. A practical and well-known example is the construction of a computational model in the form of an "artificial society", by which researchers can analyze the structure of a social system. (Wikipedia).
Using images and video data for social science: Challenges and opportunities
Speakers: Bryce Dietrich (Assistant Professor of Social Science Informatics at the University of Iowa), Laura Nelson (Assistant Professor of Sociology at Northeastern University), Michelle Torres (Assistant Professor of Political Science at Rice), and Han Zhang (SICSS-Hong Kong 21; Assista
From playlist All Videos
Computational Linguistics, by Lucas Freitas
As computers become more and more present in our lives, making our interactions with them more intuitive and natural is essential. Computational linguistics refers to the field of computer science that uses computer science to do interesting things with natural language. Examples of large
From playlist CS50 Seminars 2013
SketchySVD - Joel Tropp, California Institute of Technology
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai
From playlist Mathematics of data: Structured representations for sensing, approximation and learning
The Scientific Method and the question of "Infinite Sets" | Sociology and Pure Maths| N J Wildberger
Let's get some kind of serious discussion going about the differences in methodology and philosophy between the sciences and mathematics, and how these differences manifest themselves in the attitude towards the logical foundations of mathematics. In particular we look at a bulwark notio
From playlist Sociology and Pure Mathematics
Optimal transport for machine learning - Gabriel Peyre, Ecole Normale Superieure
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai
From playlist Mathematics of data: Structured representations for sensing, approximation and learning
The mother of all representer theorems for inverse problems & machine learning - Michael Unser
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai
From playlist Mathematics of data: Structured representations for sensing, approximation and learning
SICSS 2017 - Why SICSS? (Day 1. June 19, 2017)
The first Summer Institute in Computational Social Science was held at Princeton University from June 18 to July 1, 2017, sponsored by the Russell Sage Foundation. For more details, please visit https://compsocialscience.github.io/summer-institute/2017/
From playlist SICSS 2017 - Introduction (6/19)
SICSS 2019 -- Jobs in Computational Social Science
From playlist SICSS 2019
Introduction to Computational Linguistics
http://users.umiacs.umd.edu/~jbg/teaching/CMSC_723/
From playlist Computational Linguistics I
An Introduction to Text Analysis
In this video Professor Chris Bail of Duke University gives an introduction to quantitative text analysis for computational social scientists. Link to the slides used in this presentation: https://compsocialscience.github.io/summer-institute/2020/materials/day3-text-analysis/intro-text-ana
From playlist SICSS 2020
Curt Jaimungal Interview and Theories of Everything | Sociology and Pure Maths | N J Wildberger
In a recent interview that Curt Jaimungal did with me on "Real Numbers aren't Real", we touched upon the idea of reversing roles, that is me interviewing him, and this conversation is the result. Curt has a background in mathematics and physics and has worked as a film maker in Toronto.
From playlist Sociology and Pure Mathematics
Fellow Short Talks: Dr Gian Marco Campagnolo, Edinburgh University
Bio I am Lecturer in Science, Technology & Innovation Studies at the University of Edinburgh. My research highlights aspects of business knowledge as apparent in client-consultant relationships as well as vendor-user interaction or in special conditions such as IT symposia and software de
From playlist Short Talks
Is pure mathematics logically viable? Five Challenges! | Sociology and Pure Maths | N J Wildberger
Some tough talk directed towards the professoriat and students of the subject: is it time to re-evaluate what exactly is going on in Pure Mathematics? This is part of a series on the Sociology of Pure Mathematics, where we try to delve into and unravel some of the mysteries of the profess
From playlist Sociology and Pure Mathematics
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Nicholas Christakis: The Sociological Science Behind Social Networks and Social Influence
The Sociological Science Behind Social Networks and Social Influence Watch the newest video from Big Think: https://bigth.ink/NewVideo Join Big Think Edge for exclusive videos: https://bigth.ink/Edge ---------------------------------------------------------------------------------- If you
From playlist The Floating University Sessions | Big Think
Web 2.0 Expo NY 2011, Duncan Watts, Yahoo! Research, "The Myth of Common Sense"
The Myth of Common Sense: Why Everything That Seems Obvious Isn't More info: http://www.web2expo.com/webexny2011/public/schedule/detail/21096 Duncan Watts is a principal research scientist at Yahoo! Research, where he directs the Human Social Dynamics group. Prior to joining Yahoo!, he w
From playlist Web 2.0 Expo New York 2011
Stanford Seminar - How Behavior Spreads
EE380: Computer Systems Colloquium Seminar "How Behavior Spreads" Speaker: Damon Centola, University of Pennsylvania About the talk: New social movements, technologies, and public-health initiatives often struggle to take off, yet many diseases disperse rapidly without issue. Can the les
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Machine Learning