16,314 research outputs found

    Implementing spatial segregation measures in R.

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    Reliable and accurate estimation of residential segregation between population groups is important for understanding the extent of social cohesion and integration in our society. Although there have been considerable methodological advances in the measurement of segregation over the last several decades, the recently developed measures have not been widely used in the literature, in part due to their complex calculation. To address this problem, we have implemented several newly proposed segregation indices in R, an open source software environment for statistical computing and graphics, as a package called seg. Although there are already a few standalone applications and add-on packages that provide access to similar methods, our implementation has a number of advantages over the existing tools. First, our implementation is flexible in the sense that it provides detailed control over the calculation process with a wide range of input parameters. Most of the parameters have carefully chosen defaults, which perform acceptably in many situations, so less experienced users can also use the implemented functions without too much difficulty. Second, there is no need to export results to other software programs for further analysis. We provide coercion methods that enable the transformation of our output classes into general R classes, so the user can use thousands of standard and modern statistical techniques, which are already available in R, for the post-processing of the results. Third, our implementation does not require commercial software to operate, so it is accessible to a wider group of people

    The F@ Framework of Designing Awareness Mechanisms in Instant Messaging

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    This paper presents our research on awareness support in Instant Messaging (IM). The paper starts with a brief overview of empirical study of IM, using an online survey and face-to-face interviews to identify user needs for awareness support. The study identified a need for supporting four aspects of awareness, awareness of multiple concurrent conversations, conversational awareness, presence awareness of a group conversation, and visibility of moment-to-moment listeners and viewers. Based on the empirical study and existing research on awareness, we have developed the F@ (read as fat) framework of awareness. F@ comprises of the abstract level and the concrete level. The former includes an in-depth description of various awareness aspects in IM, whilst the latter utilises temporal logic to formalise fundamental time-related awareness aspects. F@ helps developers gain a better understanding of awareness and thereby design usable mechanisms to support awareness. Applying F@, we have designed several mechanisms to support various aspect of awareness in IM
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