Spectral Analysis of Multiscale Cultural Traits on Twitter

Abstract

Understanding and mapping the emergence and boundaries of cultural areas is a challenge for social sciences. In this paper, we present a method for analyzing the cultural composition of regions via Twitter hashtags. Cultures can be described as distinct combination of traits which we capture via principal component analysis (PCA). We investigate the top 8 PCA components of an area including France, Spain, and Portugal, in terms of the geographic distribution of their hashtag composition. We also discuss relationships between components and the insights those relationships can provide into the structure of a cultural space. Finally, we compare the spatial autocorrelation of PCA components in the Twitter data to similar components resulting from the Axelrod model. We conclude that properties of Twitter behavior can be framed in the discussion of cultural emergence and collective learning.