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The Challenges of Cultural Segmentation: New Approaches from Computational Social Science

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Methods and Instruments in the Study of Meaning-Making

Abstract

In this chapter, we explore a selection of computational methods that are being discussed in the context of cognitive sociology research for the purpose of cultural segmentation. While there is no perfect solution, these methods provide potential insights into identifying implicit cognitive schemata and their distribution across a population by means of samples. In particular, we will discuss two more theory-driven methods, Relational Class Analysis and Concept Association Task, and one method that is more based on the principles of statistical learning and data-driven, model-based recursive partitioning. From different angles, all three methods discussed can be applied to the task of cultural segmentation if combined with the use of proper large samples of participants. We will discuss the three approaches, their strengths and their shortcomings in their application to potential cultural segmentation.

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Veltri, G.A. (2023). The Challenges of Cultural Segmentation: New Approaches from Computational Social Science. In: Salvatore, S., Veltri, G.A., Mannarini, T. (eds) Methods and Instruments in the Study of Meaning-Making. Culture in Policy Making: The Symbolic Universes of Social Action. Springer, Cham. https://doi.org/10.1007/978-3-031-21995-5_2

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  • DOI: https://doi.org/10.1007/978-3-031-21995-5_2

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