Optimising influence in social networks using bounded rationality models

Kasthurirathna, Dharshana; Harré, Michael; Piraveenan, Mahendra

doi:10.1007/s13278-016-0367-4

Cited by 8 publications

(6 citation statements)

References 38 publications

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“…Furthermore, the scale-free topology seems to emerge independently of the games considered by [21]. Since then, the framework and results of [21] have been used in problems relating to internet routing [22] and optimising influence in social networks [23]. Here, we argue that the optimal topology to maximise rational behaviour among all players depends on the games under consideration, and in no case does it correspond to a scale-free network.…”

Section: Introductionmentioning

confidence: 90%

Topology-dependent rationality and quantal response equilibria in structured populations

Roman

Brede

2017

Phys. Rev. E

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Given that the assumption of perfect rationality is rarely met in the real world, we explore a graded notion of rationality in socioecological systems of networked actors. We parametrize an actors' rationality via their place in a social network and quantify system rationality via the average Jensen-Shannon divergence between the games Nash and logit quantal response equilibria. Previous work has argued that scale-free topologies maximize a system's overall rationality in this setup. Here we show that while, for certain games, it is true that increasing degree heterogeneity of complex networks enhances rationality, rationality-optimal configurations are not scale-free. For the Prisoner's Dilemma and Stag Hunt games, we provide analytic arguments complemented by numerical optimization experiments to demonstrate that core-periphery networks composed of a few dominant hub nodes surrounded by a periphery of very low degree nodes give strikingly smaller overall deviations from rationality than scale-free networks. Similarly, for the Battle of the Sexes and the Matching Pennies games, we find that the optimal network structure is also a core-periphery graph but with a smaller difference in the average degrees of the core and the periphery. These results provide insight on the interplay between the topological structure of socioecological systems and their collective cognitive behavior, with potential applications to understanding wealth inequality and the structural features of the network of global corporate control.

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Section: Introductionmentioning

confidence: 90%

Topology-dependent rationality and quantal response equilibria in structured populations

Roman

Brede

2017

Phys. Rev. E

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“…En ese sentido, los individuos se apoyan en la opinión o conocimiento de un experto en el tema o de un grupo de personas con una amplia plataforma que es de su interés. Precisamente, en el caso de los influencers, muchas personas toman en consideración lo que hacen, dicen y sugieren, dado que, al tener una gran audiencia, confían en que las decisiones que toman son óptimas para su público (Kasthurirathna et al, 2016).…”

Section: Racionalidad Limitadaunclassified

¿El comportamiento de los influencers puede influir en la toma de decisiones de los consumidores e inversionistas?

Castillo,

Cordier,

Patilongo

et al. 2024

dee

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El objetivo de la presente investigación es comprobar si el comportamiento de los influencers orienta en alguna dirección la decisión de compra de los consumidores. En ese sentido, se desarrollan algunas nociones de la teoría económica que explican la conducta que adoptan los consumidores cuando toman decisiones basadas en la recomendación de un tercero: la racionalidad limitada, las reglas heurísticas, los animal spirits y el efecto “manada”. Con la finalidad de alcanzar el objetivo, se analizan diversos casos en los que el actuar de los influencers es la razón principal por la que el valor de un activo, bien o servicio se modifica en el mercado. Aplicar las nociones económicas a casos reales brindará una mejor explicación del efecto de su accionar y ayudará a comprender y explicar el porqué de la importancia de estos actores. De lo investigado se concluye que los influencers sí generan un impacto en la decisión del consumidor, el cual se evidencia en el precio de las acciones.

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“…These models first appeared in the field of physics which remains a significant source of inspiration for CE [14,15], as does the mathematics of network theory [10,16] and evolution [17,18], ideas that have been brought together in work on evolutionary game theory on networks in order to understand the emergence of cooperation [19] and spreading dynamics over networks [20]. On the topic of evolution in economics, Brian Arthur, who coined the termed 'complexity economics', has written [21]: ... because complexity economics looks at how structures form or solutions come to be 'selected', it connects robustly with the dynamics of evolutionary economics.…”

Section: Introduction 1the Economics Of Heterogeneity and Interconnec...mentioning

confidence: 99%

“…Within the context of complexity economics, this article reviews several recent research directions at multiple different levels of analysis as well as some of the work that we have carried out in recent years. This includes our work on applied network theory [20,[51][52][53][54], bifurcations and systemic risks [55][56][57][58][59][60], agent-based modelling of economic markets [61][62][63][64], the theoretical limits of 'rationality' and strategic choice [20,[65][66][67][68][69], and how information theory can be used to understand the dynamics of these systems [70][71][72][73][74][75][76][77]. The purpose then is to place this research in the context of the work being carried out in other groups around the world.…”

Section: Introduction 1the Economics Of Heterogeneity and Interconnec...mentioning

confidence: 99%

Complexity Economics in a Time of Crisis: Heterogeneous Agents, Interconnections, and Contagion

Harré

Eremenko

Glavatskiy

et al. 2021

Systems

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In this article, we consider a variety of different mechanisms through which crises such as COVID-19 can propagate from the micro-economic behaviour of individual agents through to an economy’s aggregate dynamics and subsequently spill over into the global economy. Our central theme is one of changes in the behaviour of heterogeneous agents, agents who differ in terms of some measure of size, wealth, connectivity, or behaviour, in different parts of an economy. These are illustrated through a variety of case studies, from individuals and households with budgetary constraints, to financial markets, to companies composed of thousands of small projects, to companies that implement single multi-billion dollar projects. In each case, we emphasise the role of data or theoretical models and place them in the context of measuring their inter-connectivity and emergent dynamics. Some of these are simple models that need to be `dressed’ in socio-economic data to be used for policy-making, and we give an example of how to do this with housing markets, while others are more similar to archaeological evidence; they provide hints about the bigger picture but have yet to be unified with other results. The result is only an outline of what is possible but it shows that we are drawing closer to an integrated set of concepts, principles, and models. In the final section, we emphasise the potential as well as the limitations and what the future of these methods hold for economics.

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Optimising influence in social networks using bounded rationality models

Cited by 8 publications

References 38 publications

Topology-dependent rationality and quantal response equilibria in structured populations

Topology-dependent rationality and quantal response equilibria in structured populations

¿El comportamiento de los influencers puede influir en la toma de decisiones de los consumidores e inversionistas?

Complexity Economics in a Time of Crisis: Heterogeneous Agents, Interconnections, and Contagion

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