Models, Algorithms, and Software in the Social
In recent years, formal models in psychology have changed their status from ‘nice to have’
to ‘absolutely essential’. This is good for us, because these models come with fascinating
mathematical backgrounds and with interesting challenges for the software implementation;
in other words, they are great fun, and finally we have a reason to take a close look at them if
we are interested in humans and society.
In this working group, we will investigate some algorithms and software challenges that
occur in the social sciences. These may come from four areas of social science software,
1. algorithms to find parameter estimates in models via Least Squares, Maximum Like-
lihood, or Bayesian Estimation,
2. algorithms to work with big data, for example EEG or MRT data, including clustering and
3. cognitive and social models like neural networks, decision models, or swarm based mo-
4. Monte-Carlo simulations to evaluate how well statistical methods work under what condi-
tions and to predict future outcomes.
The participants will be asked to implement some algorithms (in any programing language
they fancy) in teams of two (preferably one with a stronger focus on programming and the
other with a stronger focus on application) and present their algorithm, its uses in psychology
or other social sciences, and its implementation. We will offer a number of algorithms, but we
are also looking forward to your own suggestions if you have already programmed an algo-
rithm in the past that you would like to present.
Prof. Dr. Timo von Oertzen
Professur für Methodenlehre und Evaluation, Universität der Bundeswehr, München
Prof. Steven Boker, Ph.D.
Quantitative Psychology, Department of Psychology, University of Virginia / USA
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Akademie Krakau International