Influence of Supporters’ Purposeful Movement on Effectiveness of Propaganda

Conventional wisdom holds that growing a supporter base strengthens propaganda via the bandwagon effect; yet, real-world outcomes often show the opposite. We investigate why larger bases can coincide with lower conversion rates among undecided individuals. Using an agent-based simulation that incorporates a Schelling-style movement rule, we run nine scenarios across three competitive regimes (balanced, competitor-strong, propagandist-strong) with supporter shares ranging from 10%–33%. We find: (1) purposeful movement (preference-driven relocation) induces spatial clustering that reduces cross-type exposure, leading clustered supporters to consistently underperform dispersed supporters; (2) when supporters on both sides exhibit purposeful movement, a numerically inferior side could gain an advantage under certain conditions (e.g., when the opponent clusters more); and (3) excessive increases in supporter numbers—which promote strong spatial clustering—can erode a dominant propagandist’s edge. The mechanism is straightforward: clustering satisfies in-group preferences but isolates supporters from the undecided, muting the bandwagon effect. These results qualify the presumed linear link between supporter volume and campaign success and offer practical guidance: prioritize maintaining supporter dispersion over simply maximizing numbers (e.g., broad geographic reach rather than concentrated rallies). Our framework is reproducible and points to extensions involving heterogeneous agents, nonlinear persuasion, and diverse network topologies.

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Publication Details

Journal
Journal of Advanced Computational Intelligence and Intelligent Informatics
Published
2026-05-19
DOI
https://doi.org/10.20965/jaciii.2026.p0689
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
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article

Influence of Supporters’ Purposeful Movement on Effectiveness of Propaganda

Journal of Advanced Computational Intelligence and Intelligent Informatics
Opinion Dynamics and Social Influence
article

Influence of Supporters’ Purposeful Movement on Effectiveness of Propaganda

article en

Abstract

Conventional wisdom holds that growing a supporter base strengthens propaganda via the bandwagon effect; yet, real-world outcomes often show the opposite. We investigate why larger bases can coincide with lower conversion rates among undecided individuals. Using an agent-based simulation that incorporates a Schelling-style movement rule, we run nine scenarios across three competitive regimes (balanced, competitor-strong, propagandist-strong) with supporter shares ranging from 10%–33%. We find: (1) purposeful movement (preference-driven relocation) induces spatial clustering that reduces cross-type exposure, leading clustered supporters to consistently underperform dispersed supporters; (2) when supporters on both sides exhibit purposeful movement, a numerically inferior side could gain an advantage under certain conditions (e.g., when the opponent clusters more); and (3) excessive increases in supporter numbers—which promote strong spatial clustering—can erode a dominant propagandist’s edge. The mechanism is straightforward: clustering satisfies in-group preferences but isolates supporters from the undecided, muting the bandwagon effect. These results qualify the presumed linear link between supporter volume and campaign success and offer practical guidance: prioritize maintaining supporter dispersion over simply maximizing numbers (e.g., broad geographic reach rather than concentrated rallies). Our framework is reproducible and points to extensions involving heterogeneous agents, nonlinear persuasion, and diverse network topologies.

Journal of Advanced Computational Intelligence and Intelligent InformaticsVol. 30(3)
Tokyo Institute of Technology (JP), Kanto Gakuin University (JP)
Openalex Percentile: Top 5%
Opinion Dynamics and Social Influence
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Influence of Supporters’ Purposeful Movement on Effectiveness of Propaganda · Journal of Advanced Computational Intelligence and Intelligent Informatics (2026) | TGRS Research Map | TGRS