Keywords, citations and ‘algorithm magic’: exploring assumptions about ranking in academic literature searches online

Author:

Jordan Katy1ORCID,Tsai Sally Po2ORCID

Affiliation:

1. Department of Educational Research, Lancaster University, Lancaster, UK

2. Faculty of Education, University of Cambridge, Cambridge, UK

Publisher

Informa UK Limited

Reference56 articles.

1. Expanding on the Frames: Making a Case for Algorithmic Literacy

2. Relevance ranking is not relevance ranking or, when the user is not the user, the search results are not search results

3. Baker S. E. and R. Edwards 2012. “How Many Qualitative Interviews Is Enough?” NCRM. https://eprints.ncrm.ac.uk/id/eprint/2273/.

4. Beel, J., and B. Gipp 2009a. “Google Scholar’s Ranking Algorithm: An Introductory Overview.” In Proceedings of ISSI 2009 : 12th International Conference on Scientometrics and Informetrics, International Society for Scientometrics and Informetrics, edited by B. Larsen and J. Leta, Rio de Janeiro (Brazil), Accessed July 2009. https://docear.org/papers/Google%20Scholar's%20Ranking%20Algorithm%20–%20An%20Introductory%20Overview%20–%20preprint.pdf.

5. Beel, J., and B. Gipp 2009b. “Google Scholar’s Ranking Algorithm: The Impact of Articles’ Age (an Empirical Study).” Sixth International Conference on Information Technology: New Generations, 160–164, Las Vegas, Nevada, USA. https://doi.org/10.1109/ITNG.2009.317.

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