Territorial Developments Based on Graffiti: a Statistical Mechanics Approach

TL;DR

This paper models gang territory formation using a statistical mechanics approach, showing that graffiti alone can drive clustering and phase transitions without direct gang interactions.

Contribution

It introduces a two-gang Hamiltonian model based on graffiti interactions, revealing that gang clustering can occur solely due to graffiti effects, a novel insight.

Findings

Gang clustering can arise from graffiti interactions alone.

Phase transitions between mixed and clustered states depend on model parameters.

Graffiti-driven clustering can occur without direct gang-to-gang interactions.

Abstract

We study the well-known sociological phenomenon of gang aggregation and territory formation through an interacting agent system defined on a lattice. We introduce a two-gang Hamiltonian model where agents have red or blue affiliation but are otherwise indistinguishable. In this model, all interactions are indirect and occur only via graffiti markings, on-site as well as on nearest neighbor locations. We also allow for gang proliferation and graffiti suppression. Within the context of this model, we show that gang clustering and territory formation may arise under specific parameter choices and that a phase transition may occur between well-mixed, possibly dilute configurations and well separated, clustered ones. Using methods from statistical mechanics, we study the phase transition between these two qualitatively different scenarios. In the mean-field rendition of this model, we identify parameter regimes where the transition is first or second order. In all cases, we have found that the transitions are a consequence solely of the gang to graffiti couplings, implying that direct gang to gang interactions are not strictly necessary for gang territory formation; in particular, graffiti may be the sole driving force behind gang clustering. We further discuss possible sociological -- as well as ecological -- ramifications of our results.