Opinion Dynamics and Collective Risk Perception:An Agent-Based Model of Institutional and Media Communication About Disasters

The behavior of a heterogeneous population of individuals during an emergency, such as epidemics, natural disasters, terrorist attacks, is dynamic, emergent and complex. In this situation, reducing uncertainty about the event is crucial in order to identify and pursue the best possible course of action. People depend on experts, government sources, the media and fellow community members as potentially valid sources of information to reduce uncertainty, but their messages can be ambiguous, misleading or contradictory. Effective risk prevention depends on the way in which the population receives, elaborates and spread the message, and together these elements result in a collective perception of risk. The interaction between individuals' attitudes toward risk and institutions, the more or less alarmist way in which the information is reported and the role of the media can lead to risk perception that differs from the original message, as well as to contrasting opinions about risk within the same population. The aim of this study is to bridge a model of opinion dynamics with the issue of uncertainty and trust in the sources, in order to understand the determinants of collective risk assessment. Our results show that alarming information spreads more easily than reassuring one, and that the media plays a key role in this. Concerning the role of internal variables, our simulation results show that risk sensitiveness has more influence on the final opinion than trust towards the institutional message. Furthermore, the role of different network structures seemed to be negligible, even on two empirically calibrated network topologies, thus suggesting that knowing beforehand how much the public trusts their institutional representatives and how reactive they are to a certain risk might provide useful indications to design more effective communication strategies during crises

NDlib: a python library to model and analyze diffusion processes over complex networks

Nowadays the analysis of dynamics of and on networks represents a hot topic in the social network analysis playground. To support students, teachers, developers and researchers, in this work we introduce a novel framework, namely NDlib, an environment designed to describe diffusion simulations. NDlib is designed to be a multi-level ecosystem that can be fruitfully used by different user segments. For this reason, upon NDlib, we designed a simulation server that allows remote execution of experiments as well as an online visualization tool that abstracts its programmatic interface and makes available the simulation platform to non-technicians

Opinion leader detection in Asian social networks using modified spider monkey optimization

The Asian social networks are dominated by the society’s collectivist culture, and this interestingly introduces a influence mechanism aided by word-of-mouth and opinion leaders. An opinion leader can help to generate and shape other people’s opinion and achieve a high information spread on any topic. In this work, a modified spider monkey optimization based opinion leader detection approach is proposed. Firstly, we employ the modified node2vec graph embedding to generate the lower dimensional vectors which act as the initial features for the nodes in a typical Asian social network. Next the entire population is broken down into several groups using the k-means++ algorithm where the number of clusters is equal to the number of opinion leaders to be selected. The local and global leaders are chosen by using the coordinates of the cluster centres of these clusters. The coordinates of the centroids of the clusters are then used to detect the local and global leaders in the network. The local leaders then form the seed set of opinion leaders for the network. The positions of the nodes in the network, including the local and global leaders, are updated over a number of iterations. At the end of these iterations, the seed set generating the maximum influence forms the set of opinion leaders in the network. We test our proposed approach using the popular information diffusion and cognitive opinion dynamics (COD) models. We perform intensive experiments on several real-life social networks based on various performance metrics. The results obtained reveal that the proposed approach outperforms several existing techniques of opinion leader detection

The drivers of Corporate Social Responsibility in the supply chain. A case study.

Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and how its CSR strategies reflect on its suppliers and customers relations. Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the generalizing capacity of these findings. Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy. Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of sustainable innovation. Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”

The Romantic zeitgeist in post-Cold War international relations and the disintegration of Yugoslavia.

The post-Cold War 1990s were pervaded by a popular sense of pessimism and decline. The thesis argues that such sentiments were part of a general mood in international relations towards Romanticism. It examines how this Romantic sensibility affected interpretations of conflict in Yugoslavia, outlines Romantic predictions about post-Cold War conflict, and compares the Romantic view with a structural perspective of Yugoslavia's demise. The thesis uses a variety of methods, including a philosophical exploration of Romanticism in the nineteenth century and the 1990s, a literary analysis of key texts on conflict, an empirical investigation of armed conflict data, and a theoretical treatment of structural factors in conflict. The thesis historicises nineteenth-century Romanticism as a reaction to the uncertainties created by three transformations: political revolution in France, Industrial Revolution in Britain, and cultural revolution in Germany. It then examines Romanticism through five themes-anti-rationalism, pessimism, nostalgia, relativism, and nature. It compares the 1990s and its 'revolutions'-fragmentation and globalization-developing the concept of Postmodern Romanticism within these themes and applies them to trends in 1990s international relations. Further, the thesis examines Romantic interpretations of conflict in the works of Robert Kaplan, Samuel Huntington, and Martin van Creveld, specifically scrutinising their interpretations of conflict in Yugoslavia. It then empirically investigates various Romantic predictions about conflict, providing empirical evidence that these predictions are inaccurate. Building on the empirical analyses that find state creation rather than identity differences an important factor in conflict, the thesis develops an alternative theoretical framework for assessing state stability based on four structural risk factors: colonial legacy, political institutions, economic structure, and demographic shifts, introducing agency through the concepts of exit, voice, and loyalty. The thesis uses this framework to compare Romantic and structural views of conflict in Yugoslavia. Finally, it provides some reflections on 1990s Romanticism and conflict