61 research outputs found
Opinion Polarization by Learning from Social Feedback
We explore a new mechanism to explain polarization phenomena in opinion
dynamics in which agents evaluate alternative views on the basis of the social
feedback obtained on expressing them. High support of the favored opinion in
the social environment, is treated as a positive feedback which reinforces the
value associated to this opinion. In connected networks of sufficiently high
modularity, different groups of agents can form strong convictions of competing
opinions. Linking the social feedback process to standard equilibrium concepts
we analytically characterize sufficient conditions for the stability of
bi-polarization. While previous models have emphasized the polarization effects
of deliberative argument-based communication, our model highlights an affective
experience-based route to polarization, without assumptions about negative
influence or bounded confidence.Comment: Presented at the Social Simulation Conference (Dublin 2017
The approach towards equilibrium in a reversible Ising dynamics model -- an information-theoretic analysis based on an exact solution
We study the approach towards equilibrium in a dynamic Ising model, the Q2R
cellular automaton, with microscopic reversibility and conserved energy for an
infinite one-dimensional system. Starting from a low-entropy state with
positive magnetisation, we investigate how the system approaches equilibrium
characteristics given by statistical mechanics. We show that the magnetisation
converges to zero exponentially. The reversibility of the dynamics implies that
the entropy density of the microstates is conserved in the time evolution.
Still, it appears as if equilibrium, with a higher entropy density is
approached. In order to understand this process, we solve the dynamics by
formally proving how the information-theoretic characteristics of the
microstates develop over time. With this approach we can show that an estimate
of the entropy density based on finite length statistics within microstates
converges to the equilibrium entropy density. The process behind this apparent
entropy increase is a dissipation of correlation information over increasing
distances. It is shown that the average information-theoretic correlation
length increases linearly in time, being equivalent to a corresponding increase
in excess entropy.Comment: 15 pages, 2 figure
The rise of populism and the reconfiguration of the German political space
The paper explores the notion of a reconfiguration of political space in the
context of the rise of populism and its effects on the political system. We
focus on Germany and the appearance of the new right wing party "Alternative
for Germany" (AfD). Many scholars of politics discuss the rise of the new
populism in Western Europe and the US with respect to a new political cleavage
related to globalization, which is assumed to mainly affect the cultural
dimension of the political space. As such, it might replace the older economic
cleavage based on class divisions in defining the dominant dimension of
political conflict. An explanation along these lines suggests a reconfiguration
of the political space in the sense that (1) the main cleavage within the
political space changes its direction from the economic axis towards the
cultural axis, but (2) also the semantics of the cultural axis itself is
changing towards globalization related topics. Using the electoral manifestos
from the Manifesto project database, we empirically address this
reconfiguration of the political space by comparing political spaces for
Germany built using topic modeling with the spaces based on the content
analysis of the Manifesto project and the corresponding categories of political
goals. We find that both spaces have a similar structure and that the AfD
appears on a new dimension. In order to characterize this new dimension we
employ a novel technique, inter-issue consistency networks (IICN) that allow to
analyze the evolution of the correlations between the political positions on
different issues over several elections. We find that the new dimension
introduced by the AfD can be related to the split off of a new "cultural right"
issue bundle from the previously existing center-right bundle
Unique Information and Secret Key Decompositions
The unique information () is an information measure that quantifies a
deviation from the Blackwell order. We have recently shown that this quantity
is an upper bound on the one-way secret key rate. In this paper, we prove a
triangle inequality for the , which implies that the is never greater
than one of the best known upper bounds on the two-way secret key rate. We
conjecture that the lower bounds the two-way rate and discuss implications
of the conjecture.Comment: 7 page
Quantifying unique information
We propose new measures of shared information, unique information and
synergistic information that can be used to decompose the multi-information of
a pair of random variables with a third random variable . Our
measures are motivated by an operational idea of unique information which
suggests that shared information and unique information should depend only on
the pair marginal distributions of and . Although this
invariance property has not been studied before, it is satisfied by other
proposed measures of shared information. The invariance property does not
uniquely determine our new measures, but it implies that the functions that we
define are bounds to any other measures satisfying the same invariance
property. We study properties of our measures and compare them to other
candidate measures.Comment: 24 pages, 2 figures. Version 2 contains less typos than version
Information Decomposition and Synergy
Recently, a series of papers addressed the problem of decomposing the information of two random variables into shared information, unique information and synergistic information. Several measures were proposed, although still no consensus has been reached. Here, we compare these proposals with an older approach to define synergistic information based on the projections on exponential families containing only up to k-th order interactions. We show that these measures are not compatible with a decomposition into unique, shared and synergistic information if one requires that all terms are always non-negative (local positivity). We illustrate the difference between the two measures for multivariate Gaussians.EC/FP7/31872
Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? Furthermore, how does social media play into this? Drawing on neuroscientific insights into the processing of social feedback, we develop a theoretical model that allows us to address these questions. In repeated interactions, individuals learn whether their opinion meets public approval and refrain from expressing their standpoint if it is socially sanctioned. In a social network sorted around opinions, an agent forms a distorted impression of public opinion enforced by the communicative activity of the different camps. Even strong majorities can be forced into silence if a minority acts as a cohesive whole. On the other hand, the strong social organisation around opinions enabled by digital platforms favours collective regimes in which opposing voices are expressed and compete for primacy in public. This paper highlights the role that the basic mechanisms of social information processing play in massive computer-mediated interactions on opinions
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