Trending #hijabfashion: Using Big Data to Study Religion at the Online–Urban Interface

Abstract

This article discusses the potential and the limitations of big data analysis for the study of religion. While big data analysis is often perceived as overtly positivistic because of its quantitative and computational nature, we argue instead that it lends itself to an inductive approach. Since the data are typically not collected for the purpose of testing specific hypotheses, it can best be seen as a resource for serendipitous exploration. We therefore pose a number of substantive research questions regarding the global circulation and local mediation of sartorial styles and practices among Muslim women. We present an analysis of the #hijabfashion hashtag on Instagram, drawing on a database of 15 million posts. The analysis proceeds in two steps. First, we research the deterritorialized global networks formed by users who mark their posts with the hashtag, showing how hijabistas form relationships that cut across national, ethnic, and other boundaries. Then, we demonstrate how these global networks are underpinned and powered by localized networks, focusing on the case of Rotterdam. We show how hijabistas in this Dutch city develop their religious and fashion styles through localized agglomeration economies and counterpublics. Keywords Hijab fashion network analysis big data social media Instagram

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