Minority Health and Health Equity Archive

Permanent URI for this collectionhttp://hdl.handle.net/1903/21769

Welcome to the Minority Health and Health Equity Archive (MHHEA), an electronic archive for digital resource materials in the fields of minority health and health disparities research and policy. It is offered as a no-charge resource to the public, academic scholars and health science researchers interested in the elimination of racial and ethnic health disparities.

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Subject: search.filters.subject.Population Models

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Now showing 1 - 3 of 3
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    Spreading Gossip in Social Networks
    (2007) Lind, Pedro; da Silva, Luciano; Andrade, Jr., Jose; Herrmann, Hans
    We study a simple model of information propagation in social networks, where two quantities are introduced:the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.
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    Extremism Propagation in Social Networks with Hubs
    (2008) Franks, Daniel W.; Noble, Jason; Kaufman, Peter; Stagl, Sigrid
    One aspect of opinion change that has been of academic interest is the impact of people with extreme opinions (extremists) on opinion dynamics. An agent-based model has been used to study the role of small-world social network topologies on general opinion change in the presence of extremists. It has been found that opinion convergence to a single extreme occurs only when the average number of network connections for each individual is extremely high. Here, we extend the model to examine the effect of positively skewed degree distributions, in addition to small-world structures, on the types of opinion convergence that occur in the presence of extremists. We also examine what happens when extremist opinions are located on the well-connected nodes (hubs) created by the positively skewed distribution. We find that a positively skewed network topology encourages opinion convergence on a single extreme under a wider range of conditions than topologies whose degree distributions were not skewed. The importance of social position for social influence is highlighted by the result that, when positive extremists are placed on hubs, all population convergence is to the positive extreme even when there are twice as many negative extremists. Thus, our results have shown the importance of considering a positively skewed degree distribution, and in particular network hubs and social position, when examining extremist transmission.
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    Agent-based model for friendship in social networks
    (2009) Singer, H.M.
    A model is proposed to understand the structuring of social networks in a fixed setting such as, for example,inside a university. The friendship formation is based on the frequency of encounters and mutual interest. The model shows distinctive single-scale behavior and reproduces accurately the measurable experimental quantities such as clustering coefficients, degree distribution, degree correlation, and friendship distribution. The model produces self-organized community structures and can be described as a network of densely interconnected networks. For the friendships, we find that the mutual interest is the dominant factor, which optimizes the network and that the number of encounters determines the statistically relevant distributions.