271 research outputs found
Voting contagion: modeling and analysis of a century of U.S. presidential elections
Sem informaçãoSocial influence plays an important role in human behavior and decisions. Sources of influence can be divided as external, which are independent of social context, or as originating from peers, such as family and friends. An important question is how to disentangle the social contagion by peers from external influences. While a variety of experimental and observational studies provided insight into this problem, identifying the extent of contagion based on large-scale observational data with an unknown network structure remains largely unexplored. By bridging the gap between the large-scale complex systems perspective of collective human dynamics and the detailed approach of social sciences, we present a parsimonious model of social influence, and apply it to a central topic in political science-elections and voting behavior. We provide an analytical expression of the county vote-share distribution, which is in excellent agreement with almost a century of observed U.S. presidential election data. Analyzing the social influence topography over this period reveals an abrupt phase transition from low to high levels of social contagion, and robust differences among regions. These results suggest that social contagion effects are becoming more instrumental in shaping large-scale collective political behavior, with implications on democratic electoral processes and policies.125130Sem informaçãoSem informaçãoSem informaçã
Molecular Model of Dynamic Social Network Based on E-mail communication
In this work we consider an application of physically inspired sociodynamical model to the modelling of the evolution of email-based social network. Contrary to the standard approach of sociodynamics, which assumes expressing of system dynamics with heuristically defined simple rules, we postulate the inference of these rules from the real data and their application within a dynamic molecular model. We present how to embed the n-dimensional social space in Euclidean one. Then, inspired by the Lennard-Jones potential, we define a data-driven social potential function and apply the resultant force to a real e-mail communication network in a course of a molecular simulation, with network nodes taking on the role of interacting particles. We discuss all steps of the modelling process, from data preparation, through embedding and the molecular simulation itself, to transformation from the embedding space back to a graph structure. The conclusions, drawn from examining the resultant networks in stable, minimum-energy states, emphasize the role of the embedding process projecting the non–metric social graph into the Euclidean space, the significance of the unavoidable loss of information connected with this procedure and the resultant preservation of global rather than local properties of the initial network. We also argue applicability of our method to some classes of problems, while also signalling the areas which require further research in order to expand this applicability domain
A dynamic model of time-dependent complex networks
The characterization of the "most connected" nodes in static or slowly
evolving complex networks has helped in understanding and predicting the
behavior of social, biological, and technological networked systems, including
their robustness against failures, vulnerability to deliberate attacks, and
diffusion properties. However, recent empirical research of large dynamic
networks (characterized by connections that are irregular and evolve rapidly)
has demonstrated that there is little continuity in degree centrality of nodes
over time, even when their degree distributions follow a power law. This
unexpected dynamic centrality suggests that the connections in these systems
are not driven by preferential attachment or other known mechanisms. We present
a novel approach to explain real-world dynamic networks and qualitatively
reproduce these dynamic centrality phenomena. This approach is based on a
dynamic preferential attachment mechanism, which exhibits a sharp transition
from a base pure random walk scheme.Comment: 8 pages, 6 figures; This is a substantial revision of the previous
versio
Anticipating economic market crises using measures of collective panic
Sem informaçãoPredicting panic is of critical importance in many areas of human and animal behavior, notably in the context of economics. The recent financial crisis is a case in point. Panic may be due to a specific external threat or self-generated nervousness. Here we show that the recent economic crisis and earlier large single-day panics were preceded by extended periods of high levels of market mimicry-direct evidence of uncertainty and nervousness, and of the comparatively weak influence of external news. High levels of mimicry can be a quite general indicator of the potential for self-organized crises.Predicting panic is of critical importance in many areas of human and animal behavior, notably in the context of economics. The recent financial crisis is a case in point. Panic may be due to a specific external threat or self-generated nervousness. Here we show that the recent economic crisis and earlier large single-day panics were preceded by extended periods of high levels of market mimicry-direct evidence of uncertainty and nervousness, and of the comparatively weak influence of external news. High levels of mimicry can be a quite general indicator of the potential for self-organized crises.107127Sem informaçãoSem informaçãoSem informaçã
A Universal Model of Global Civil Unrest
Civil unrest is a powerful form of collective human dynamics, which has led
to major transitions of societies in modern history. The study of collective
human dynamics, including collective aggression, has been the focus of much
discussion in the context of modeling and identification of universal patterns
of behavior. In contrast, the possibility that civil unrest activities, across
countries and over long time periods, are governed by universal mechanisms has
not been explored. Here, we analyze records of civil unrest of 170 countries
during the period 1919-2008. We demonstrate that the distributions of the
number of unrest events per year are robustly reproduced by a nonlinear,
spatially extended dynamical model, which reflects the spread of civil disorder
between geographic regions connected through social and communication networks.
The results also expose the similarity between global social instability and
the dynamics of natural hazards and epidemics.Comment: 8 pages, 3 figure
Path homology and temporal networks
We present an algorithm to compute path homology for simple digraphs, and use
it to topologically analyze various small digraphs en route to an analysis of
complex temporal networks which exhibit such digraphs as underlying motifs. The
digraphs analyzed include all digraphs, directed acyclic graphs, and undirected
graphs up to certain numbers of vertices, as well as some specially constructed
cases. Using information from this analysis, we identify small digraphs
contributing to path homology in dimension for three temporal networks, and
relate these digraphs to network behavior. We conclude that path homology can
provide insight into temporal network structure and vice versa
10 Years of C-K Theory: A Survey on the Academic and Industrial Impacts of a Design Theory.
The goal of our research1 was to understand what is expected today from a design theory and what types of impact such type of scientific proposition may reach. To answer these questions with a grounded approach we chosed to study the developement of C-K theory as phenomenon per se that can inform our research work. C-K theory is clearly recognized as a design theory and it is a good representative of the level of generality and abstraction of contemporary design theory. Indeed, the validity of the theory as such has already been documented (e.g. Hatchuel & Weil 2002, 2003, 2008, 2009; Kazakçi 2009; Reich et al 2010; Le Masson et al 2010; Ullah et al 2012). Instead the current work sets out to understand the dissemination and the impact of the theory in both academic and industrial fields. The data collection overlooks the literature on C-K theory in English and in French, and includes interviews and feedbacks of students and industrial partners who applied C-K methodologies and tools. This research confirms the rapid diffusion and multiples impact of C-K theory. Beyond, such study signals that there are important expectations and potential impacts of a Design Theory within the field of knowledge at large. However there are strong conditions to meet these expectations: generality, generativity, and relatedness to contemporary sciences. A similar research could be done on Nam Suh's axiomatic approach to further test these conditions. It is impossible to say what will be the next generations of Design theory but it is sure that they should progress on these directions
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