Using artificial neural networks to simulate social category learning: A tutorial

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Abstract

This tutorial introduces the use of connectionist (or artificial neural network) computational modeling to understand mechanisms for social psychological phenomena. We explain how modeling requires researchers to make explicit their assumptions and make concrete their operationalizations for hypothesized mechanisms. The tutorial walks readers through the conceptual steps of how to design an artificial neural network based on Lei et al. (2020), and how to implement key theoretical assumptions. The tutorial is also accompanied by a detailed and commented technical guide available on the Open Science Framework. The model replicated key findings from past behavioral data and provides support for hypothesized theoretical assumptions. Implications for how and why researchers might incorporate modeling into their own research and theorizing are discussed.

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