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Human social relationships, often grounded in kinship, are being fundamentally altered by globalization as integration into geographically distant markets disrupts traditional kin based social networks. Religion plays a significant role in regulating social networks and may both stabilize extant networks as well as create new ones in ways that are under-recognized during the process of market integration. Here we use a detailed survey assessing the social networks of women in rural Bangladesh to examine whether religiosity preserves bonds among kin or broadens social networks to include fellow practitioners, thereby replacing genetic kin with unrelated co-religionists. Results show that the social networks of more religious women are larger and contain more kin but not more non-kin. More religious women’s networks are also more geographically diffuse and differ from those of less religious women by providing more emotional support, but not helping more with childcare or offering more financial assistance. Overall, these results suggest that in some areas experiencing rapid social, economic, and demographic change, religion, in certain contexts, may not serve to broaden social networks to include non-kin, but may rather help to strengthen ties between relatives and promote family cohesion.

Disrupting the emergence and evolution of potentially violent online extremist movements is a crucial challenge. Extremism research has analyzed such movements in detail, focusing on individual- and movement-level characteristics. But are there system-level commonalities in the ways these movements emerge and grow? Here we compare the growth of the Boogaloos, a new and increasingly prominent U.S. extremist movement, to the growth of online support for ISIS, a militant, terrorist organization based in the Middle East that follows a radical version of Islam. We show that the early dynamics of these two online movements follow the same mathematical order despite their stark ideological, geographical, and cultural differences. The evolution of both movements, across scales, follows a single shockwave equation that accounts for heterogeneity in online interactions. These scientific properties suggest specific policies to address online extremism and radicalization. We show how actions by social media platforms could disrupt the onset and ‘flatten the curve’ of such online extremism by nudging its collective chemistry. Our results provide a system-level understanding of the emergence of extremist movements that yields fresh insight into their evolution and possible interventions to limit their growth.

We show that malicious COVID-19 content, including racism, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond the control of any individual social media platform. We provide a first mapping of the online hate network across six major social media platforms. We demonstrate how malicious content can travel across this network in ways that subvert platform moderation efforts. Machine learning topic analysis shows quantitatively how online hate communities are sharpening COVID-19 as a weapon, with topics evolving rapidly and content becoming increasingly coherent. Based on mathematical modeling, we provide predictions of how changes to content moderation policies can slow the spread of malicious content.