Polarization of coalitions in an agent-based model of political discourse

Political discourse is the verbal interaction between political actors in a policy domain. This article explains the formation of polarized advocacy or discourse coalitions in this complex phenomenon by presenting a dynamic, stochastic, and discrete agent-based model based on graph theory and local optimization. In a series of thought experiments, actors compute their utility of contributing a specific statement to the discourse by following ideological criteria, preferential attachment, agenda-setting strategies, governmental coherence, or other mechanisms. The evolving macro-level discourse is represented as a dynamic network and evaluated against arguments from the literature on the policy process. A simple combination of four theoretical mechanisms is already able to produce artificial policy debates with theoretically plausible properties. Any sufficiently realistic configuration must entail innovative and path-dependent elements as well as a blend of exogenous preferences and endogenous opinion formation mechanisms

Feigenbaum graphs: a complex network perspective of chaos

The recently formulated theory of horizontal visibility graphs transforms time series into graphs and allows the possibility of studying dynamical systems through the characterization of their associated networks. This method leads to a natural graph-theoretical description of nonlinear systems with qualities in the spirit of symbolic dynamics. We support our claim via the case study of the period-doubling and band-splitting attractor cascades that characterize unimodal maps. We provide a universal analytical description of this classic scenario in terms of the horizontal visibility graphs associated with the dynamics within the attractors, that we call Feigenbaum graphs, independent of map nonlinearity or other particulars. We derive exact results for their degree distribution and related quantities, recast them in the context of the renormalization group and find that its fixed points coincide with those of network entropy optimization. Furthermore, we show that the network entropy mimics the Lyapunov exponent of the map independently of its sign, hinting at a Pesin-like relation equally valid out of chaos.Comment: Published in PLoS ONE (Sep 2011

Dynamics of Opinion Forming in Structurally Balanced Social Networks

A structurally balanced social network is a social community that splits into two antagonistic factions (typical example being a two-party political system). The process of opinion forming on such a community is most often highly predictable, with polarized opinions reflecting the bipartition of the network. The aim of this paper is to suggest a class of dynamical systems, called monotone systems, as natural models for the dynamics of opinion forming on structurally balanced social networks. The high predictability of the outcome of a decision process is explained in terms of the order-preserving character of the solutions of this class of dynamical systems. If we represent a social network as a signed graph in which individuals are the nodes and the signs of the edges represent friendly or hostile relationships, then the property of structural balance corresponds to the social community being splittable into two antagonistic factions, each containing only friends

Developing an online learning community for mental health professionals and service users: a discursive analysis

<p>Abstract</p> <p>Background</p> <p>There is increasing interest in online collaborative learning tools in health education, to reduce costs, and to offer alternative communication opportunities. Patients and students often have extensive experience of using the Internet for health information and support, and many health organisations are increasingly trying out online tools, while many healthcare professionals are unused to, and have reservations about, online interaction.</p> <p>Methods</p> <p>We ran three week-long collaborative learning courses, in which 19 mental health professionals (MHPs) and 12 mental health service users (MHSUs) participated. Data were analysed using a discursive approach to consider the ways in which participants interacted, and how this contributed to the goal of online learning about using Internet technologies for mental health practice.</p> <p>Results</p> <p>MHSUs and MHPs were able to discuss issues together, listening to the views of the other stakeholders. Discussions on synchronous format encouraged participation by service users while the MHPs showed a preference for an asynchronous format with longer, reasoned postings. Although participants regularly drew on their MHP or MHSU status in discussions, and participants typically drew on either a medical expert discourse or a "lived experience" discourse, there was a blurred boundary as participants shifted between these positions.</p> <p>Conclusions</p> <p>The anonymous format was successful in that it produced a "co-constructed asymmetry" which permitted the MHPs and MHSUs to discuss issues online, listening to the views of other stakeholders. Although anonymity was essential for this course to 'work' at all, the recourse to expert or lay discourses demonstrates that it did not eliminate the hierarchies between teacher and learner, or MHP and MHSU. The mix of synchronous and asynchronous formats helped MHSUs to contribute. Moderators might best facilitate service user experience by responding within an experiential discourse rather than an academic one.</p

Beyond equilibrium climate sensitivity

ISSN:1752-0908ISSN:1752-089