Polarized Ukraine 2014: Opinion and Territorial Split Demonstrated with the Bounded Confidence XY Model, Parameterized by Twitter Data

Multiple countries have recently experienced extreme political polarization, which in some cases led to escalation of hate crime, violence and political instability. Beside the much discussed presidential elections in the United States and France, Britain’s Brexit vote and Turkish constitutional referendum, showed signs of extreme polarization. Among the countries affected, Ukraine faced some of the gravest consequences. In an attempt to understand the mechanisms of these phenomena, we here combine social media analysis with agent-based modeling of opinion dynamics, targeting Ukraine’s crisis of 2014. We use Twitter data to quantify changes in the opinion divide and parameterize an extended Bounded-Confidence XY Model, which provides a patiotemporal description of the polarization dynamics.We demonstrate that the level of emotional intensity is a major driving force for polarization that can lead to a spontaneous onset of collective behavior at a certain degree of homophily and conformity. We find that the critical level of emotional intensity corresponds to a polarization transition, marked by a sudden increase in the degree of involvement and in the opinion bimodality

Choice modelling with Gaussian processes in the social sciences: A case study of neighbourhood choice in Stockholm

We present a non-parametric extension of the conditional logit model, using Gaussian process priors. The conditional logit model is used in quantitative social science for inferring interaction effects between personal features and choice characteristics from observations of individual multinomial decisions, such as where to live, which car to buy or which school to choose. The classic, parametric model presupposes a latent utility function that is a linear combination of choice characteristics and their interactions with personal features. This imposes strong and unrealistic constraints on the form of individuals’ preferences. Extensions using non-linear basis functions derived from the original features can ameliorate this problem but at the cost of high model complexity and increased reliance on the user in model specification. In this paper we develop a non-parametric conditional logit model based on Gaussian process logit models. We demonstrate its application on housing choice data from over 50,000 moving households from the Stockholm area over a two year period to reveal complex homophilic patterns in income, ethnicity and parental status

The effects of communicating climate change threat: mobilizing anger and authoritarian affect displacement

Research on climate change communication has made important contributions to our understanding of how to effectively inform and mobilize the public for climate action and yet open questions remain, not least because existing results are at times inconclusive or incomplete. The climate crisis poses an existential threat. But what effect does communicating that threat have? To what degree can communicating the threat invoke anger and how does anger interact with individual values predispositions? In this study, we conducted a survey experiment (N = 570) to better understand effects of communicating climate change threat. We find that exposure to climate change threat makes people angrier, and anger makes them more willing to act on climate change mitigation, confirming previous findings. However, our study adds a novel insight, the findings do not apply to people with authoritarian predispositions. They display lower levels of anger and willingness to act, while exposure to climate change threat results in increased authoritarian attitudes. This suggests that climate change threat can lead to affect displacement in people with authoritarian predispositions, where anger (typically directed at those in power, who have failed to tackle climate change) is redirected at non-conforming groups

Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation

It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena display nonlinearities. In this article, we introduce a new modeling tool in order to partly fill this void in the literature. Using data of all secondary schools in Stockholm county during the years 1990 to 2002, we demonstrate how the methodology can be applied to identify complex dynamic patterns like tipping points and multiple phase transitions with respect to segregation. We establish critical thresholds in schools’ ethnic compositions, in general, and in relation to various factors such as school quality and parents’ income, at which the schools are likely to tip and become increasingly segregated

Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation

It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena display nonlinearities. In this article, we introduce a new modeling tool in order to partly fill this void in the literature. Using data of all secondary schools in Stockholm county during the years 1990 to 2002, we demonstrate how the methodology can be applied to identify complex dynamic patterns like tipping points and multiple phase transitions with respect to segregation. We establish critical thresholds in schools’ ethnic compositions, in general, and in relation to various factors such as school quality and parents’ income, at which the schools are likely to tip and become increasingly segregated

Relating industrial symbiosis and circular economy to the sustainable development debate

Industrial Symbiosis (IS) is a business-focused collaborative approach oriented towards resource efficiency that has been theorised and studied mainly over the last twenty-five years. Recently, IS seems to have found a renewed impetus in the framework of the Circular Economy (CE), a novel approach to sustainability and Sustainable Development (SD) that has been rapidly gaining momentum world-wide. This opening chapter of the book provides an introduction to the concepts of IS, CE and SD, and summarizes their complex evolutionary paths, recalling the rel-evant developments and implementation challenges. In addition, the authors point out the divergences and interrelations of these concepts, both among themselves and with other related concepts and research fields, such as industrial ecology, eco-logical modernization and the green economy. Furthermore, the potential contribu-tion of IS and the CE to SD is briefly discussed, also highlighting critical issues and trade-offs, as well as gaps in research and application, especially relating to the so-cial component of sustainability. Particular attention is given to the potential role of IS in the achievement of targets connected to the Sustainable Development Goals set in the UN Agenda 2030. The recent advances in the IS and CE discussion in the context of the SD research community are further explored, with particular empha-sis on the contribution of the International Sustainable Development Research So-ciety (ISDRS) and its 24th annual conference organised in Messina, Italy, in 2018. The programme of that conference, indeed, included specific tracks on the above-mentioned themes, the contents of which are briefly commented on here, after an overview on the whole conference and the main cross-cutting concepts emerged. In the last part of the chapter, a brief description of the chapters collected in the book is presented. These contributions describe and discuss theoretical frameworks, methodological approaches and/or experiences and case studies where IS and the principles of CE are applied in different geographical context and at different scales to ultimately improve the sustainability of the current production patterns