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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,

which are

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

classifier algorithms,

3. cognitive and social models like neural networks, decision models, or swarm based mo-

dels, and

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