137,356 research outputs found

    Quantifying the long-term influence of scientific publications

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    We consider the long-term indirect influence of publications on subsequent publications. In particular, we are here interested in long-term scientific influence at the level of disciplines. We present a novel method to quantify the long-term scientific influence of publications, considering both direct and indirect, or higher-order citations. We apply this method to Web of Science data at the level of disciplines. Preliminary results for a specific operationalization of the notion of long-term scientific influence suggest that long-term influence is dominated by a few disciplines: Astronomy and Astrophysics, Basic Life Sciences, and Physics and Material Science.</p

    Quantifying the long-term influence of scientific publications

    Get PDF
    We consider the long-term indirect influence of publications on subsequent publications. In particular, we are here interested in long-term scientific influence at the level of disciplines. We present a novel method to quantify the long-term scientific influence of publications, considering both direct and indirect, or higher-order citations. We apply this method to Web of Science data at the level of disciplines. Preliminary results for a specific operationalization of the notion of long-term scientific influence suggest that long-term influence is dominated by a few disciplines: Astronomy and Astrophysics, Basic Life Sciences, and Physics and Material Science.</p

    Will This Paper Increase Your h-index? Scientific Impact Prediction

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    Scientific impact plays a central role in the evaluation of the output of scholars, departments, and institutions. A widely used measure of scientific impact is citations, with a growing body of literature focused on predicting the number of citations obtained by any given publication. The effectiveness of such predictions, however, is fundamentally limited by the power-law distribution of citations, whereby publications with few citations are extremely common and publications with many citations are relatively rare. Given this limitation, in this work we instead address a related question asked by many academic researchers in the course of writing a paper, namely: "Will this paper increase my h-index?" Using a real academic dataset with over 1.7 million authors, 2 million papers, and 8 million citation relationships from the premier online academic service ArnetMiner, we formalize a novel scientific impact prediction problem to examine several factors that can drive a paper to increase the primary author's h-index. We find that the researcher's authority on the publication topic and the venue in which the paper is published are crucial factors to the increase of the primary author's h-index, while the topic popularity and the co-authors' h-indices are of surprisingly little relevance. By leveraging relevant factors, we find a greater than 87.5% potential predictability for whether a paper will contribute to an author's h-index within five years. As a further experiment, we generate a self-prediction for this paper, estimating that there is a 76% probability that it will contribute to the h-index of the co-author with the highest current h-index in five years. We conclude that our findings on the quantification of scientific impact can help researchers to expand their influence and more effectively leverage their position of "standing on the shoulders of giants."Comment: Proc. of the 8th ACM International Conference on Web Search and Data Mining (WSDM'15
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