2014Proceedings of the American Society for Information Science and TechnologyOpen access

Uncertainty of author citation rankings: Lessons from in‐text citation weighing schemes

Andreas Strotmann, Dangzhi Zhao

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Abstract

ABSTRACT In‐text frequency‐weighted citation counting has been seen as a particularly promising solution to the well‐known problem of citation analysis that treats all citations equally, be they crucial to the citing paper or perfunctory. But what is a good weighting scheme? Our preliminary results show that the ranks of authors in the field of Library and Information Science vary wildly with different in‐text citation frequency weighting schemes, suggesting that author citation ranks may inherently be uncertain.

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ABSTRACT In‐text frequency‐weighted citation counting has been seen as a particularly promising solution to the well‐known problem of citation analysis that treats all citations equally, be they crucial to the citing paper or perfunctory. But what is a good weighting scheme? Our preliminary results show that the ranks of authors in the field of Library and Information Science vary wildly with different in‐text citation frequency weighting schemes, suggesting that author citation ranks may inherently be uncertain.

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Available abstract

ABSTRACT In‐text frequency‐weighted citation counting has been seen as a particularly promising solution to the well‐known problem of citation analysis that treats all citations equally, be they crucial to the citing paper or perfunctory. But what is a good weighting scheme? Our preliminary results show that the ranks of authors in the field of Library and Information Science vary wildly with different in‐text citation frequency weighting schemes, suggesting that author citation ranks may inherently be uncertain.

Key concepts: Citation, Weighting, Scheme (mathematics), Computer science, Field (mathematics), Citation analysis, Information retrieval, Data science

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