A Survey on Nonstrategic Models of Opinion Dynamics

The paper presents a survey on selected models of opinion dynamics. Both discrete (more precisely, binary) opinion models as well as continuous opinion models are discussed. We focus on frameworks that assume non-Bayesian updating of opinions. In the survey, a special attention is paid to modeling nonconformity (in particular, anticonformity) behavior. For the case of opinions represented by a binary variable, we recall the threshold model, the voter and q-voter models, the majority rule model, and the aggregation framework. For the case of continuous opinions, we present the DeGroot model and some of its variations, time-varying models, and bounded confidence models.

Lattice Studies of Gerrymandering Strategies

A new theoretical method for examining gerrymandering is presented based on lattice models of voters, in which districts are constructed by partitioning the lattice. We propose three novel algorithms for constructing equal-population, connected districts which favor the gerrymanderer and incorporate the spatial distribution of voters. Due to the probabilistic population fluctuations inherent to our voter models, Monte Carlo techniques can be applied to study the impact of gerrymandering. We use the method developed here to compare our different gerrymandering algorithms, show approaches which ignore spatial data lead to (legally prohibited) disconnected districts, and examine the effectiveness of isoperimetric quotient tests.

The Fifth Troll Prerequisite

Chapter 8 focuses on the fifth troll prerequisite which needed to be met if hacked and Russian-generated content were to influence the U.S. election: was it targeted to reach the desired constituencies? The chapter contends that, despite some arguments against the impact of the Russian troll messaging, the trolls targeted audiences needed to influence the election in both battleground and nonbattleground states, through the use of organic content and paid advertisements. The trolls had access to multiple sources of information about how to reach voters susceptible to mobilizing or demobilizing appeals, including publicly accessible analyses of the candidates’ objectives and tactics, stolen voter models hacked from the Democratic Congressional Campaign Committee, and toolkits offered by social media platforms to help identify desired audience members.

Scaling laws and criticality in voter models and neuronal dynamics

<p class="p1">Una propiedad importante de muchos sistemas complejos es la presencia de leyes de escalamiento, las cuales se caracterizan por el hecho de que las variables que describen el comportamiento del sistema se relacionan a través de leyes de potencias. Las leyes de escalamiento generalmente tienen dos implicaciones importantes: (i) la auto–similitud del sistema en un gran rango de escalas (cada parte del sistema se parece al sistema completo), y, (ii) los “eventos raros” (es decir, eventos poco probables) no son tan raros y ocurren mucho más frecuentemente de lo que se esperaría. En este trabajo discutimos la criticalidad dinámica como uno de los principales mecanismos que generan leyes de escalamiento en sistemas complejos, enfocándonos principalmente en modelos de formación de opiniones y en redes neuronales. Veremos que dos sistemas aparentemente muy distintos (redes de votantes y redes neuronales) pueden describirse prácticamente con las mismas herramientas conceptuales y metodológicas, lo cual ilustra la universalidad de los fenómenos críticos y las correspondientes leyes de escalamiento.<span class="Apple-converted-space"> </span></p>