Modeling birds on wires

Aydoğdu, Aylin; Frasca, Paolo; D’Apice, Ciro; Manzo, Rosanna; Thornton, Janet; Gachomo, B.; Wilson, Th.A.; Cheung, Brandon; Tariq, Usman; Saidel, William M.; Piccoli, Benedetto

doi:10.1016/j.jtbi.2016.11.026

Cited by 8 publications

(10 citation statements)

References 23 publications

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“…In online social media, users exchange opinions via the contents they share: out of a randomly generated pool of fresh contents, the online platform selects for each user the best contents in order to maximize engagement, mainly based on similarities between users [5]. Limitations of attention have also been considered in biology by a number of theoretical and experimental studies about flocking in animal groups [6], [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Opinion Dynamics With Topological Gossiping: Asynchronous Updates Under Limited Attention

Rossi

Frasca

2020

IEEE Control Syst. Lett.

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This paper introduces a general model of opinion dynamics with opinion-dependent connectivity. Agents update their opinions asynchronously: for the updating agent, the new opinion is the average of the k closest opinions within a subset of m agents that are sampled from the population of size n. Depending on k and m with respect to n, the dynamics can have a variety of equilibria, which include consensus and clustered configurations. The model covers as special cases a classical gossip update (if m = n) and a deterministic update defined by the k nearest neighbors (if m = k). We prove that the dynamics converges to consensus if n > 2(m − k). Before convergence, however, the dynamics can remain for long time in the vicinity of metastable clustered configurations.

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Section: Introductionmentioning

confidence: 99%

Opinion Dynamics With Topological Gossiping: Asynchronous Updates Under Limited Attention

Rossi

Frasca

2020

IEEE Control Syst. Lett.

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“…If x σ(i) (0) < x σ(j) (0), then x σ(i) (t) < x σ(j) (t) for t > 0 by Proposition 1. If x σ(i) (0) = x σ(j) (0), then N σ(i) = N σ(j) and therefore x σ(i) (t) = x σ(j) (t) also for t > 0 by (3).…”

Section: ⊓ ⊔mentioning

confidence: 99%

“…Users interact via the contents they share: out of the pool of fresh contents, the online platform selects for each user the best contents in order to maximize engagement, mainly based on similarities between users [23]. As the notion of Dunbar number was originally defined with reference to primates, the reader will not find surprising that similar ideas have also been fundamental in the study of flocking in animal groups, as testified by numerous theoretical and experimental works [5,20,15,24,3]. The importance of considering networks where the number of neighbors is limited has also been understood by graph theorists, who have studied the properties of what they call k-nearest-neighbors graph: for instance, it is known that k must be logarithmic in n to ensure connectivity [4].…”

Section: Introductionmentioning

confidence: 99%

Modeling limited attention in opinion dynamics by topological interactions

Ceragioli¹,

Frasca²,

Rossi³

2020

Preprint

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This work explores models of opinion dynamics with opiniondependent connectivity. Our starting point is that individuals have limited capabilities to engage in interactions with their peers. Motivated by this observation, we propose a continuous-time opinion dynamics model such that interactions take place with a limited number of peers: we refer to these interactions as topological, as opposed to metric interactions that are postulated in classical bounded-confidence models. We observe that topological interactions produce equilibria that are very robust to disruptions.

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“…In a striking contrast, this observation has been made in the field of biology by a number of quantitative studies about flocking in animal groups (these include both theoretical and experimental works) [6,7,8,9]. The importance of this way of defining connectivity has been also captured by graph theorists, who have studied a the properties of what they call k-nearest-neighbors graph.…”

Section: Introductionmentioning

confidence: 99%

Asynchronous opinion dynamics on the <tex>$k$</tex>-nearest-neighbors graph

Rossi

Frasca

2018

2018 IEEE Conference on Decision and Control (CDC)

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This paper is about a new model of opinion dynamics with opiniondependent connectivity. We assume that agents update their opinions asynchronously and that each agent's new opinion depends on the opinions of the k agents that are closest to it. We show that the resulting dynamics is substantially different from comparable models in the literature, such as bounded-confidence models. We study the equilibria of the dynamics, observing that they are robust to perturbations caused by the introduction of new agents. We also prove that if the number of agents n is smaller than 2k, the dynamics converge to consensus. This condition is only sufficient.

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Modeling birds on wires

Cited by 8 publications

References 23 publications

Opinion Dynamics With Topological Gossiping: Asynchronous Updates Under Limited Attention

Opinion Dynamics With Topological Gossiping: Asynchronous Updates Under Limited Attention

Modeling limited attention in opinion dynamics by topological interactions

Asynchronous opinion dynamics on the <tex>$k$</tex>-nearest-neighbors graph

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