Building a Computational Model for Mapping Religious Identity and Cultural Belonging among African Diaspora Communities

Abstract

Standard sociological and anthropological perspectives have a tendency to brush aside and/or partly ignore the unique and resides of present-day African diaspora communities. Both of these ideas – assimilation and migration – are classically qualitative and contradict each other, and the article omits the potential for classical quantitative analysis methods which would be appropriate to this day's transnational communities and the effect of the digital media. Considering these gaps in the theoretical and methodological aspects, this conceptual paper offers the innovative combination of Agent-Based Modeling (ABM) and Natural Language Processing (NLP) as a computational framework.  The architecture is conceived as an ongoing dynamic and interactive process between the micro-level behaviour simulations of different cohorts of agents and the macro-level text-mining of real digital footprints created by different people around the world, such as online discussions, social media, and transnational religious broadcasting. The framework is used to operationalize intangible sociological variables such as religious affiliation, cultural hybridity scores, transnational tie strength, generational cohorts, and host-society integration rates that impact on the individual choice and long term cultural evolution. Beyond that, there is a risk assessment matrix to responds to algorithmic bias, data privacy and model validation. In sum, the interdisciplinary connection is a full-fledged simulation tool that can be used by researchers, policy makers and community leaders to explore cultural resilience, to predict generational changes, and to identify and develop multicultural, inclusive communities