On the normalization and visualization of author co‐citation data: Salton's Cosine versus the Jaccard index

Loet Leydesdorff

Journal of the American Society for Information Science and Technology, 2008, vol. 59, issue 1, 77-85

Abstract: The debate about which similarity measure one should use for the normalization in the case of Author Co‐citation Analysis (ACA) is further complicated when one distinguishes between the symmetrical co‐citation—or, more generally, co‐occurrence—matrix and the underlying asymmetrical citation—occurrence—matrix. In the Web environment, the approach of retrieving original citation data is often not feasible. In that case, one should use the Jaccard index, but preferentially after adding the number of total citations (i.e., occurrences) on the main diagonal. Unlike Salton's cosine and the Pearson correlation, the Jaccard index abstracts from the shape of the distributions and focuses only on the intersection and the sum of the two sets. Since the correlations in the co‐occurrence matrix may be spurious, this property of the Jaccard index can be considered as an advantage in this case.

Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (34)

Downloads: (external link)
https://doi.org/10.1002/asi.20732

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jamist:v:59:y:2008:i:1:p:77-85

Ordering information: This journal article can be ordered from
https://doi.org/10.1002/(ISSN)1532-2890

Access Statistics for this article

More articles in Journal of the American Society for Information Science and Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().