112,563 research outputs found

    ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives

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    This paper presents ATEM, a novel framework for studying topic evolution in scientific archives. ATEM is based on dynamic topic modeling and dynamic graph embedding techniques that explore the dynamics of content and citations of documents within a scientific corpus. ATEM explores a new notion of contextual emergence for the discovery of emerging interdisciplinary research topics based on the dynamics of citation links in topic clusters. Our experiments show that ATEM can efficiently detect emerging cross-disciplinary topics within the DBLP archive of over five million computer science articles

    Enhancing project-related behavioral competence in education

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    The workforce has increasingly been demanding an educational model that produces students experienced in real project management (PM) practices. This includes producing technically competent students--one who can manage real-world project constraints of cost and schedule but also possess critical project related behavioral competence. Such soft skills are essential if a project is to run smoothly and eventually succeed. In this paper, we describe an educational framework grounded in outcomes based education to enhance project-related behavioral competence. Instructors can leverage this framework to augment their existing courses and develop the critical career skill sets of graduating students

    COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts

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    © 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00066The COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indicators during 21 March to 18 April 2020. The rapidly increasing volume of research, is particularly accessible through Dimensions, and less through Scopus, the Web of Science, and PubMed. Google Scholar’s results included many false matches. A few COVID-19 papers from the 21,395 in Dimensions were already highly cited, with substantial news and social media attention. For this topic, in contrast to previous studies, there seems to be a high degree of convergence between articles shared in the social web and citation counts, at least in the short term. In particular, articles that are extensively tweeted on the day first indexed are likely to be highly read and relatively highly cited three weeks later. Researchers needing wide scope literature searches (rather than health focused PubMed or medRxiv searches) should start with Dimensions (or Google Scholar) and can use tweet and Mendeley reader counts as indicators of likely importance
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