Online social platforms have become a fertile ground for the rapid spread of extremist narratives, yet traditional single‐layer network analyses overlook the interplay of content, timing, and polarization that fuels radicalization. We introduce the Integrated Multilayer Reinforcement Model (IMRM), a unified framework that represents each user as a node in four interdependent layers (interaction, content similarity, temporal dynamics, and sentiment) and explicitly encodes feedback loops via uniform interlayer coupling. We define three novel measures: Composite Reinforced Centrality (CRC), which multiplicatively aggregates a user’s normalized influence across layers; Temporal Burst Influence (TBI), which captures episodic surges in activity; and Sentiment Synchronization Coefficient (SSC), which quantifies emotional alignment with peers. We derive four theoretical propositions linking these measures to radicalization processes and validate them on Reddit data surrounding five major United States socio‐political events. Our experiments reveal that (i) high CRC users have a high probability of being radicalized, (ii) radicalized users have higher values of both TBI and SSC, (iii) bridging nodes linking different communities exhibit elevated CRC, and (iv) CRC remains a robust, context‐invariant predictor of radical engagement. The findings aim at highlighting how online radicalization emerges from the synergistic fusion of who you interact with, what you share, when you act, and how you feel.
Integrated Multilayer Reinforcement Model: Explaining the Dynamics of Online Radicalization
Cauteruccio, Francesco
2025
Abstract
Online social platforms have become a fertile ground for the rapid spread of extremist narratives, yet traditional single‐layer network analyses overlook the interplay of content, timing, and polarization that fuels radicalization. We introduce the Integrated Multilayer Reinforcement Model (IMRM), a unified framework that represents each user as a node in four interdependent layers (interaction, content similarity, temporal dynamics, and sentiment) and explicitly encodes feedback loops via uniform interlayer coupling. We define three novel measures: Composite Reinforced Centrality (CRC), which multiplicatively aggregates a user’s normalized influence across layers; Temporal Burst Influence (TBI), which captures episodic surges in activity; and Sentiment Synchronization Coefficient (SSC), which quantifies emotional alignment with peers. We derive four theoretical propositions linking these measures to radicalization processes and validate them on Reddit data surrounding five major United States socio‐political events. Our experiments reveal that (i) high CRC users have a high probability of being radicalized, (ii) radicalized users have higher values of both TBI and SSC, (iii) bridging nodes linking different communities exhibit elevated CRC, and (iv) CRC remains a robust, context‐invariant predictor of radical engagement. The findings aim at highlighting how online radicalization emerges from the synergistic fusion of who you interact with, what you share, when you act, and how you feel.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


