953 research outputs found

    Mean Field Voter Model of Election to the House of Representatives in Japan

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    In this study, we propose a mechanical model of a plurality election based on a mean field voter model. We assume that there are three candidates in each electoral district, i.e., one from the ruling party, one from the main opposition party, and one from other political parties. The voters are classified as fixed supporters and herding (floating) voters with ratios of 1−p1-p and pp, respectively. Fixed supporters make decisions based on their information and herding voters make the same choice as another randomly selected voter. The equilibrium vote-share probability density of herding voters follows a Dirichlet distribution. We estimate the composition of fixed supporters in each electoral district and pp using data from elections to the House of Representatives in Japan (43rd to 47th). The spatial inhomogeneity of fixed supporters explains the long-range spatial and temporal correlations. The estimated values of pp are close to the estimates obtained from a survey.Comment: 11 pages, 7 figure

    Dynamical and bursty interactions in social networks

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    We present a modeling framework for dynamical and bursty contact networks made of agents in social interaction. We consider agents' behavior at short time scales, in which the contact network is formed by disconnected cliques of different sizes. At each time a random agent can make a transition from being isolated to being part of a group, or vice-versa. Different distributions of contact times and inter-contact times between individuals are obtained by considering transition probabilities with memory effects, i.e. the transition probabilities for each agent depend both on its state (isolated or interacting) and on the time elapsed since the last change of state. The model lends itself to analytical and numerical investigations. The modeling framework can be easily extended, and paves the way for systematic investigations of dynamical processes occurring on rapidly evolving dynamical networks, such as the propagation of an information, or spreading of diseases

    COVID-19 policy analysis: labour structure dictates lockdown mobility behaviour

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    Countries and cities around the world have resorted to unprecedented mobility restrictions to combat COVID-19 transmission. Here we exploit a natural experiment whereby Colombian cities implemented varied lockdown policies based on ID number and gender to analyse the impact of these policies on urban mobility. Using mobile phone data, we find that the restrictiveness of cities' mobility quotas (the share of residents allowed out daily according to policy advice) does not correlate with mobility reduction. Instead, we find that larger, wealthier cities with more formalized and complex industrial structure experienced greater reductions in mobility. Within cities, wealthier residents are more likely to reduce mobility, and commuters are especially more likely to stay at home when their work is located in wealthy or commercially/industrially formalized neighbourhoods. Hence, our results indicate that cities' employment characteristics and work-from-home capabilities are the primary determinants of mobility reduction. This finding underscores the need for mitigations aimed at lower income/informal workers, and sheds light on critical dependencies between socio-economic classes in Latin American cities

    Research challenges in nanosatellite-DTN networks

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    Current approaches based on classical satellite communications, aimed at bringing Internet connectivity to remote and underdeveloped areas, are too expensive and impractical. Nanosatellites architectures with DTN protocol have been proposed as a cost-effective solution to extend the network access in rural and remote areas. In order to guarantee a good service and a large coverage in rural areas, it is necessary to deploy a good number of nanosatellites; consequentially, for reliability and load balancing purposes, is also needed a large number of ground stations (or hot spots) connected on the Internet. During a data connection, a server on the Internet that wants to reply to the user on rural area, has many hot spot alternatives to whom it can deliver data. Different hot spots can send data to final destination with different delivery delay depending on the number, position and buffer occupancy of satellites with which it comes into contact. The problem of choosing the optimal hot spot becomes important because a wrong choice could lead a high delivery delay

    The strength of the strongest ties in collaborative problem solving

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    Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems

    Social network dynamics of face-to-face interactions

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    The recent availability of data describing social networks is changing our understanding of the "microscopic structure" of a social tie. A social tie indeed is an aggregated outcome of many social interactions such as face-to-face conversations or phone-calls. Analysis of data on face-to-face interactions shows that such events, as many other human activities, are bursty, with very heterogeneous durations. In this paper we present a model for social interactions at short time scales, aimed at describing contexts such as conference venues in which individuals interact in small groups. We present a detailed anayltical and numerical study of the model's dynamical properties, and show that it reproduces important features of empirical data. The model allows for many generalizations toward an increasingly realistic description of social interactions. In particular in this paper we investigate the case where the agents have intrinsic heterogeneities in their social behavior, or where dynamic variations of the local number of individuals are included. Finally we propose this model as a very flexible framework to investigate how dynamical processes unfold in social networks.Comment: 20 pages, 25 figure

    Process multiplicity and process dynamics : weaving the space of possible paths

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    In research on process organization studies, the concept of multiplicity is widely used, but a fundamental confusion about what process multiplicity means persists. As a result, we miss some of the potential of this concept for understanding process dynamics and process change. In this paper, we define process multiplicity as a duality of ‘one’ and ‘many’, and we conceptualize ‘the many’ as a space of possible paths encompassed by a process. We use the notion of paths to operationalize process multiplicity and make it accessible for empirical research. When we see process as a multiplicity, process change can be understood as expanding, shifting or contracting the space of possible paths. We suggest that this concept of process multiplicity also has implications for a range of other theoretical and practical topics, including standards, standardization and flexibility as well as process replication, management and resilience

    MLP: a MATLAB toolbox for rapid and reliable auditory threshold estimation

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    In this paper, we present MLP, a MATLAB toolbox enabling auditory thresholds estimation via the adaptive Maximum Likelihood procedure proposed by David Green (1990, 1993). This adaptive procedure is particularly appealing for those psychologists that need to estimate thresholds with a good degree of accuracy and in a short time. Together with a description of the toolbox, the current text provides an introduction to the threshold estimation theory and a theoretical explanation of the maximum likelihood adaptive procedure. MLP comes with a graphical interface and it is provided with several built-in, classic psychoacoustics experiments ready to use at a mouse click
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