Crowd dynamics in historical perspective: Reframing the Amritsar massacre through agent-based modelling and social psychology

Crowds have long held a paradoxical place in the human imagination, feared for their destructive potential yet essential for collective expression. This tension was tragically manifested in the 1919 Jallianwala Bagh massacre, when British colonial troops opened fire on a peaceful gathering in Amritsar, India. Although officially 379 deaths were recorded, eyewitnesses and historians have long challenged this figure. With this study, we critically revisit the events through the lens of the specific role of the crowd as a phenomenon, both regarding the physical and the socio-psychological dynamics. Our agent-based simulations distribute the 1650 rounds that were fired over a crowd trying to leave through the five narrow openings of the documented geometry. They yield numbers of people hit above the official count under every assumption tested: 660 in the lowest case tested, half a hit per round and the smallest crowd, about 1650 for the crowd sizes that eyewitnesses reported, and 2500 at the hits per round that Wagner’s estimate implies. The openings pass at most 5850 people in ten minutes; for any larger crowd the toll is fixed by the rounds fired and the hits per round, whatever the crowd does, and the size and behaviour of the crowd decide only who falls and where: in the queues at the openings, not at the firing line. On the socio-psychological front, we explore how early 20th-century discourses, influenced by Le Bon’s theory of crowd psychology, constructed the crowd as an inherently irrational and threatening entity, thus providing a rationale for the application of excessive force. Our findings show that acknowledging the socio-cultural construction of crowds as a relevant factor in how state power engages with and respond to collective gatherings brings to light contemporary parallels and the risks posed by their rhetorical framing. Furthermore, this study highlights the importance of interdisciplinary modelling for both historical accountability and current crowd safety, particularly in an era of growing political unrest, surveillance, and militarised crowd policing.