ArticlePloS one2021
Shadowing and shielding: Effective heuristics for continuous influence maximisation in the voting dynamics.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Control over Recommendation Algorithms in Heterogeneous Modular Systems with Dynamic Opinions.Entropy (Basel, Switzerland) · 2026Article
- Speaking of Opinions: Comparing Approaches to Modelling Opinion Manipulation.La matematica · 2026Review
- Modelling the mitigation of anti-vaccine opinion propagation to suppress epidemic spread: A computational approach.PloS one · 2025Article
- Modelling opinion dynamics under the impact of influencer and media strategies.Scientific reports · 2023Article
- Sensing Enhancement on Social Networks: The Role of Network Topology.Entropy (Basel, Switzerland) · 2022Article
- Control Meets Inference: Using Network Control to Uncover the Behaviour of Opponents.Entropy (Basel, Switzerland) · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Influence maximisation, or how to affect the intrinsic opinion dynamics of a social group, is relevant for many applications, such as information campaigns, political competition, or marketing. Previous literature on influence maximisation has mostly explored discrete allocations of influence, i.e. optimally choosing a finite fixed number of nodes to target. Here, we study the generalised problem of continuous influence maximisation where nodes can be targeted with flexible intensity. We focus on optimal influence allocations against a passive opponent and compare the structure of the solutions in the continuous and discrete regimes. We find that, whereas hub allocations play a central role in explaining optimal allocations in the discrete regime, their explanatory power is strongly reduced in the continuous regime. Instead, we find that optimal continuous strategies are very well described by two other patterns: (i) targeting the same nodes as the opponent (shadowing) and (ii) targeting direct neighbours of the opponent (shielding). Finally, we investigate the game-theoretic scenario of two active opponents and show that the unique pure Nash equilibrium is to target all nodes equally. These results expose fundamental differences in the solutions to discrete and continuous regimes and provide novel effective heuristics for continuous influence maximisation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.