Religious Exiting and Social Networks: Computer Simulations of Religious/Secular Pluralism

Abstract

Statistical models attempting to predict who will disaffiliate from religions have typically accounted for less than 15% of the variation in religious affiliations, suggesting that we have only a partial understanding of this vital social process. Using agent-based simulations in three "artificial societies" (one predominantly religious; one predominantly secular; and one in between), we demonstrate that worldview pluralism within one's neighborhood and family social networks can be a significant predictor of religious (dis)affiliation but in pluralistic societies worldview diversity is less important and, instead, people move toward worldview neutrality. Our results suggest that there may be two phases in religious disaffiliation: (1) the early adopters initially disaffiliate regardless of social support, and subsequently (2) disaffiliation spreads as support for it within local social networks widens and it appears more acceptable. An important next step is for sociologists to confirm or correct the theoretical findings of this model using real-world socialnetwork data, which will require overcoming the measurement difficulties involved in estimating each individual's degree of local network pluralism.

Simulation, Science, and Stakeholders: Challenges and Opportunities for Modelling Solutions to Societal Problems

“…Te collaborative approach outlined and illustrated in Human Simulation: Perspectives, Insights, and Applications [8], is one way of addressing the challenges (and pursuing the opportunities) identifed briefy above. Tat volume describes several models developed using this approach, but it is important to note that the latter has been developed, tested, and expanded within the context of several interrelated research projects [9] that have produced a wide variety of policy-oriented computational models that provide platforms for exploring societal problems related to topics such as human terror management in response to threats such as contagion or natural hazards [10], the mutual escalation of xenophobic intergroup confict [11], the role of education and existential security in secularisation [12], the integration of minorities in western urban contexts [13], morality and (non)religious altruism [14], and social networks in pluralistic cultures [15]. Below I will spell out this approach in more detail, focusing particularly on the interaction of stakeholders and scientists in the process of analysing problems and designing solutions, but in the remainder of this section, I want to highlight some of the reasons for calling it "human" simulation.…”

Simulating Secularities: Challenges and Opportunities in the Computational Science of (Non)Religion

“…This seminar brought together three teams of computer scientists and subject matter experts for a week to work on three different models designed to explore cognitive variables and mechanisms involved in the increase of religious disbelief (analytic atheism), the growth of prosocial attitudes and behaviors among the nonreligious (altruistic atheism), and the role of social networks in exiting religion (affiliated atheism). Work on the first is still underway, but the latter two models have already been published in this special issue (Galen et al, 2021;Cragun et al, 2021).…”

“…This article is part of a special issue on "computer modeling of secularism and nonreligion," which was designed to showcase some recent contributions in the computational science of (non)religion, a rapidly growing sub-discipline in the academic study of secularism and related phenomena. While the other articles published in the special issue so far (Wildman et al, 2020;Cragun et al, 2021;Galen et al, 2021) as well as those in the pipeline, report on specific computational models that simulate some of the dynamics and mechanisms that drive secularity up (or down), this article has a broader purpose. My main goal here is to provide readers of Secularism & Nonreligion with a brief introduction to some of the challenges and opportunities that have emerged in the relatively recent application of these methodologies to the study of these topics in the social sciences and the humanities.…”

How can big data shape the field of non-religion studies? And why does it matter?

“…Gender, age, education, and geographical area are all typically associated with non-affiliation. Nevertheless, the predictive power of these socio-demographic characteristics was questioned, 63,64 suggesting that the degree of worldview pluralism Review of local networks might play a fundamental role in the process of religious non-affiliation and disaffiliation. 63 While the vast majority of social surveys do not allow respondents to elaborate further on their lack of religious affiliation, or distinguish only between atheism and agnosticism, recent research showed that generic non-religious labels hide a rich variety of internal differences ranging from new atheism to atheism plus, humanism, religious indifference, secularism, and so on.…”

“…Nevertheless, the predictive power of these socio-demographic characteristics was questioned, 63,64 suggesting that the degree of worldview pluralism Review of local networks might play a fundamental role in the process of religious non-affiliation and disaffiliation. 63 While the vast majority of social surveys do not allow respondents to elaborate further on their lack of religious affiliation, or distinguish only between atheism and agnosticism, recent research showed that generic non-religious labels hide a rich variety of internal differences ranging from new atheism to atheism plus, humanism, religious indifference, secularism, and so on. [65][66][67][68] A new comparative study of Brazil, China, Denmark, Japan, the United Kingdom, and the United States showed that only a minority of nones describe themselves as an ''atheist'' or ''agnostic,'' frequently preferring other popular labels, such as ''humanist,'' ''free-thinker,'' ''skeptic,'' ''secular,'' etc.…”