Results 31 to 40 of about 837,732 (325)

AI Pontryagin or how artificial neural networks learn to control dynamical systems

Nature Communications, 2022
Optimal control of complex dynamical systems can be challenging due to cost constraints and analytical intractability. The authors propose a machine-learning-based control framework able to learn control signals and force complex high-dimensional ...
Lucas Böttcher, Nino Antulov-Fantulin, Thomas Asikis   +2 more
doaj   +1 more source

Explaining classification performance and bias via network structure and sampling technique

Applied Network Science, 2021
Social networks are very important carriers of information. For instance, the political leaning of our friends can serve as a proxy to identify our own political preferences.
Lisette Espín-Noboa, Fariba Karimi, Bruno Ribeiro, Kristina Lerman, Claudia Wagner   +4 more
doaj   +1 more source

Group mixing drives inequality in face-to-face gatherings

Communications Physics, 2022
The emergence of inequality in social interactions can depend on a number of factors, among which the intrinsic attractiveness of individuals, but also group size the presence of pre-formed social ties.
Marcos Oliveira, Fariba Karimi, Maria Zens, Johann Schaible, Mathieu Génois, Markus Strohmaier   +5 more
doaj   +1 more source

Human social sensing is an untapped resource for computational social science

Nature, 2021
The ability to ‘sense’ the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others’ experiences.
M. Galesic, W. Bruine de Bruin, J. Dalege, S. Feld, F. Kreuter, Henrik Olsson, D. Prelec, Daniel L. Stein, Tamara van der Does   +8 more
semanticscholar   +1 more source

Computational appraisal of gender representativeness in popular movies

Humanities & Social Sciences Communications, 2021
Gender representation in mass media has long been mainly studied by qualitatively analyzing content. This article illustrates how automated computational methods may be used in this context to scale up such empirical observations and increase their ...
Antoine Mazières, Telmo Menezes, Camille Roth   +2 more
doaj   +1 more source

MANIFESTO OF COMPUTATIONAL SOCIAL SCIENCE

Mediações: Revista de Ciências Sociais, 2013
The increasing integration of technology into our lives has created unprecedented volumes of data on society’s everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems ...
Rosaria Conte, Nigel Gilbert, Giullia Bonelli, Claudio Cioffi-Revilla, Guillaume Deffuant, János Kertész, Vittorio Loreto, Suzy Moat, Jean-Pierre Nadal, Ángel Sánchez, Andrzej Nowak, Andreas Flache, Maxi San Miguel, Dirk Helbing   +13 more
doaj   +1 more source

Teaching Computational Social Science for All

PS: Political Science & Politics, 2021
Computational methods have become an integral part of political science research. However, helping students to acquire these new skills is challenging because programming proficiency is necessary, and most political science students have little coding ...
Jae Yeon Kim, Yee Man Margaret Ng
semanticscholar   +1 more source

On the accuracy of short-term COVID-19 fatality forecasts

BMC Infectious Diseases, 2022
Background Forecasting new cases, hospitalizations, and disease-induced deaths is an important part of infectious disease surveillance and helps guide health officials in implementing effective countermeasures.
Nino Antulov-Fantulin, Lucas Böttcher
doaj   +1 more source

Fame and Ultrafame: Measuring and comparing daily levels of ‘being talked about’ for United States’ presidents, their rivals, God, countries, and K-pop.

Journal of Quantitative Description: Digital Media, 2022
When building a global brand of any kind—a political actor, clothing style, or belief system— developing widespread awareness is a primary goal. Short of knowing any of the stories or products of a brand, being talked about in whatever fashion—raw
Peter Dodds, Joshua Minot, Michael Arnold, Thayer Alshaabi, Jane Adams, David Dewhurst, Andrew Reagan, Christopher Danforth   +7 more
doaj   +1 more source

How Well Do Reinforcement Learning Approaches Cope With Disruptions? The Case of Traffic Signal Control

IEEE Access, 2023
Data-driven and machine-learning-based methods are increasingly used in attempts to master the challenges of the world. But are they really the best approaches to manage complex dynamical systems?
Marcin Korecki, Damian Dailisan, Dirk Helbing   +2 more
doaj   +1 more source