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A Hybrid Semantic Approach to Building Dynamic Maps of Research Communities

机译:构建研究社区动态地图的混合语义方法

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In earlier papers we characterised the notion of diachronic topic-based communities -i.e., communities of people who work on semantically related topics at the same time. These communities are important to enable topic-centred analyses of the dynamics of the research world. In this paper we present an innovative algorithm, called Research Communities Map Builder (RCMB), which is able to automatically link diachronic topic-based communities over subsequent time intervals to identify significant events. These include topic shifts within a research community; the appearance and fading of a community; communities splitting, merging, spawning other communities; and others. The output of our algorithm is a map of research communities, annotated with the detected events, which provides a concise visual representation of the dynamics of a research area. In contrast with existing approaches, RCMB enables a much more finegrained understanding of the evolution of research communities, with respect to both the granularity of the events and the granularity of the topics. This improved understanding can, for example, inform the research strategies of funders and researchers alike. We illustrate our approach with two case studies, highlighting the main communities and events that characterized the World Wide Web and Semantic Web areas in the 2000 - 2010 decade.
机译:在较早的论文中,我们对基于历时性主题的社区(即同时从事语义相关主题的人的社区)的概念进行了描述。这些社区对于实现以主题为中心的研究世界动态分析非常重要。在本文中,我们提出了一种称为研究社区地图构建器(RCMB)的创新算法,该算法能够在随后的时间间隔内自动链接基于历时性主题的社区,以识别重大事件。这些包括研究社区内的话题转移;社区的外观和褪色;社区分裂,合并,产生其他社区;和别的。我们算法的输出是研究社区的地图,上面标注了检测到的事件,它提供了研究区域动态的简洁直观表示。与现有方法相比,RCMB可以从事件的粒度和主题的粒度两个方面更深入地了解研究社区的发展。例如,这种更好的理解可以为资助者和研究人员的研究策略提供信息。我们通过两个案例研究来说明我们的方法,重点介绍了2000年至2010年十年间互联网和语义网领域的主要社区和事件。

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