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S-index: Towards Better Metrics for Quantifying Research Impact

The ongoing growth in the volume of scientific literature available today precludes researchers from efficiently discerning the relevant from irrelevant content. Researchers are constantly interested in impactful papers, authors and venues in their respective fields. Moreover, they are interested in the so-called recent "rising stars" of these contexts which may lead to attractive directions for future work, collaborations or impactful publication venues. In this work, we address the problem of quantifying research impact in each of these contexts, in order to better direct attention of researchers and streamline the processes of comparison, ranking and evaluation of contribution. Specifically, we begin by outlining intuitive underlying assumptions that impact quantification methods should obey and evaluate when current state-of-the-art methods fail to satisfy these properties. To this end, we introduce the s-index metric which quantifies research impact through influence propagation over a heterogeneous citation network. s-index is tailored from these intuitive assumptions and offers a number of desirable qualities including robustness, natural temporality and straightforward extensibility from the paper impact to broader author and venue impact contexts. We evaluate its effectiveness on the publicly available Microsoft Academic Search citation graph with over 119 million papers and 1 billion citation edges with 103 million and 21 thousand associated authors and venues respectively.

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