Testing Google Scholar bibliographic data: Estimating error rates for Google Scholar citation parsing

  • David Zeitlyn
  • Megan Beardmore-Herd

Abstract

We present some systematic tests of the quality of bibliographic data exports available from Google Scholar. While data quality is good for journal articles and conference proceedings, books and edited collections are often wrongly described or have incomplete data. We identify a particular problem with material from online repositories.

Author Biographies

David Zeitlyn

A social anthropologist as much as he can on Mambila spider divination in Cameroon where he has been doing research since 1985. At other moments he thinks about ICT and bibliography.

Megan Beardmore-Herd

A recent Biological Anthropology BSc and Human Evolutionary Studies MPhil graduate, working as a research assistant in primatology and palaeoanthropology, ahead of studying for a DPhil in Anthropology.

Published
2018-11-01
How to Cite
Zeitlyn, D., & Beardmore-Herd, M. (2018). Testing Google Scholar bibliographic data: Estimating error rates for Google Scholar citation parsing. First Monday, 23(11). https://doi.org/10.5210/fm.v23i11.8658