Characterizing Nodes and Edges in Dynamic Attributed Networks: A Social-based Approach

How to characterize nodes and edges in dynamic attributed networks based on social aspects? We address this problem by exploring the strength of the ties between actors and their associated attributes over time, thus capturing the social roles of the actors and the meaning of their dynamic interactions in different social network scenarios. For this, we apply social concepts to promote a better understanding of the underlying complexity that involves actors and their social motivations. More specifically, we explore the notion of social capital given by the strategic positioning of a particular actor in a social structure by means of the concepts of brokerage, the ability of creating bridges with diversified patterns, and closure, the ability of aggregating nodes with similar patterns. As a result, we unveil the differences of social interactions in distinct academic coauthorship networks and questions \& answers communities. We also statistically validate our social definitions considering the importance of the nodes and edges in a social structure by means of network properties.Comment: 11 pages, 5 figure

Core-periphery organization of complex networks

Networks may, or may not, be wired to have a core that is both itself densely connected and central in terms of graph distance. In this study we propose a coefficient to measure if the network has such a clear-cut core-periphery dichotomy. We measure this coefficient for a number of real-world and model networks and find that different classes of networks have their characteristic values. For example do geographical networks have a strong core-periphery structure, while the core-periphery structure of social networks (despite their positive degree-degree correlations) is rather weak. We proceed to study radial statistics of the core, i.e. properties of the n-neighborhoods of the core vertices for increasing n. We find that almost all networks have unexpectedly many edges within n-neighborhoods at a certain distance from the core suggesting an effective radius for non-trivial network processes

You Are Only as Good as You Are Behind Closed Doors: The Stability of Virtuous Dispositions

Virtues are standardly characterized as stable dispositions. A stable disposition implies that the virtuous actor must be disposed to act well in any domain required of them. For example, a politician is not virtuous if s/he is friendly in debate with an opponent, but hostile at home with a partner or children. Some recent virtue theoretic accounts focus on specific domains in which virtues can be exercised. I call these domain-variant accounts of virtue. This paper examines two such accounts: Randall Curren and Charles Dorn’s (2018) discussion of virtue in the civic sphere, and Michael Brady’s (2018) account of virtues of vulnerability. I argue that being consistent with the standard characterization of virtue requires generalizing beyond a domain. I suggest four actions the authors could take to preserve their accounts while remaining consistent with the standard characterization. I also discuss how virtue education could be enhanced by domain-variant accounts

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

<p>Abstract</p> <p>Background</p> <p>Social networks are theorized as significant influences in the innovation adoption and behavior change processes. Our understanding of how social networks operate within healthcare settings is limited. As a result, our ability to design optimal interventions that employ social networks as a method of fostering planned behavior change is also limited. Through this proposed project, we expect to contribute new knowledge about factors influencing uptake of knowledge translation interventions.</p> <p>Objectives</p> <p>Our specific aims include: To collect social network data among staff in two long-term care (LTC) facilities; to characterize social networks in these units; and to describe how social networks influence uptake and use of feedback reports.</p> <p>Methods and design</p> <p>In this prospective study, we will collect data on social networks in nursing units in two LTC facilities, and use social network analysis techniques to characterize and describe the networks. These data will be combined with data from a funded project to explore the impact of social networks on uptake and use of feedback reports. In this parent study, feedback reports using standardized resident assessment data are distributed on a monthly basis. Surveys are administered to assess report uptake. In the proposed project, we will collect data on social networks, analyzing the data using graphical and quantitative techniques. We will combine the social network data with survey data to assess the influence of social networks on uptake of feedback reports.</p> <p>Discussion</p> <p>This study will contribute to understanding mechanisms for knowledge sharing among staff on units to permit more efficient and effective intervention design. A growing number of studies in the social network literature suggest that social networks can be studied not only as influences on knowledge translation, but also as possible mechanisms for fostering knowledge translation. This study will contribute to building theory to design such interventions.</p

Measuring Spatial Dynamics in Metropolitan Areas

This paper introduces a new approach to measuring neighborhood change. Instead of the traditional method of identifying “neighborhoods†a priori and then studying how resident attributes change over time, our approach looks at the neighborhood more intrinsically as a unit that has both a geographic footprint and a socioeconomic composition. Therefore, change is identified when both as- pects of a neighborhood transform from one period to the next. Our approach is based on a spatial clustering algorithm that identifies neighborhoods at two points in time for one city. We also develop indicators of spatial change at both the macro (city) level as well as local (neighborhood) scale. We illustrate these methods in an application to an extensive database of time-consistent census tracts for 359 of the largest metropolitan areas in the US for the period 1990-2000.

Relational contexts and conceptual model clustering

In recent years, there has been a growing interest in the use of reference conceptual models to capture information about complex and sensitive business domains (e.g., finance, healthcare, space). These models play a fundamental role in different types of critical semantic interoperability tasks. Therefore, it is essential that domain experts are able to understand and reason with their content. In other words, it is important for these reference conceptual models to be cognitively tractable. This paper contributes to this goal by proposing a model clustering technique that leverages the rich semantics of ontology-driven conceptual models (ODCM). In particular, the technique employs the notion of Relational Context to guide automated model breakdown. Such Relational Contexts capture all the information needed for understanding entities “qua players of roles” in the scope of an objectified (reified) relationship (relator)

Marketecture: A Simulation-Based Framework for Studying Experimental Deregulated Power Markets

In this paper, we present MARKETECTURE, an agent-based, microeconomic, scalable model for studying deregulated power markets. Features that distinguish it from previously studied models include: the ability to generate individualistic, demographics based, elastic demand profiles; a highly configurable system that supports different matching algorithms for buyers and sellers, different market clearing mechanisms; ability to aggregate individuals to different classes; an electrical grid to physically clear the economic contracts etc. This paper describes the model and its various features in detail. A case study is done for the city of Portland, Oregon, to evaluate the performance and efficiency of the market under different market clearing algorithms and sellers’ strategies. We analyze the structural properties of the market under different scenarios to validate our model. Our results show that if Vickrey auction clearing mechanism can induce the sellers to reveal their true production costs and bid at competitive level, the market performance can be almost pareto-efficient. The weighted average clearing method in the poolco market results in the lowest market clearing price (MCP). However, the market clearing quantity (MCQ) is also low which results in deadweight loss to the society. Our findings also show that the different orders of market execution (bilateral and poolco) can significantly affect the performance of the markets