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      Exploration of an Interdisciplinary Scientific Landscape

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          Abstract

          Patterns of interdisciplinarity in science can be quantified through diverse complementary dimensions. This paper studies as a case study the scientific environment of a generalist journal in Geography, Cybergeo, in order to introduce a novel methodology combining citation network analysis and semantic analysis. We collect a large corpus of around 200,000 articles with their abstracts and the corresponding citation network that provides a first citation classification. Relevant keywords are extracted for each article through text-mining, allowing us to construct a semantic classification. We study the qualitative patterns of relations between endogenous disciplines within each classification, and finally show the complementarity of classifications and of their associated interdisciplinarity measures. The tools we develop accordingly are open and reusable for similar large scale studies of scientific environments.

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          How Popular is Your Paper? An Empirical Study of the Citation Distribution

          S Redner (1998)
          Numerical data for the distribution of citations are examined for: (i) papers published in 1981 in journals which are catalogued by the Institute for Scientific Information (783,339 papers) and (ii) 20 years of publications in Physical Review D, vols. 11-50 (24,296 papers). A Zipf plot of the number of citations to a given paper versus its citation rank appears to be consistent with a power-law dependence for leading rank papers, with exponent close to -1/2. This, in turn, suggests that the number of papers with x citations, N(x), has a large-x power law decay N(x)~x^{-alpha}, with alpha approximately equal to 3.
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            Is science becoming more interdisciplinary? Measuring and mapping six research fields over time

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              Analyzing interdisciplinarity: Typology and indicators

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                Author and article information

                Journal
                03 December 2017
                Article
                1712.00805
                04621ad9-2232-4ebb-a9f5-5c78b8f8ce13

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                25 pages, 10 figures, 1 table
                cs.DL

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