z-logo
open-access-imgOpen Access
Appropriate similarity measures for author co‐citation analysis
Author(s) -
van Eck Nees Jan,
Waltman Ludo
Publication year - 2008
Publication title -
journal of the american society for information science and technology
Language(s) - English
Resource type - Journals
eISSN - 1532-2890
pISSN - 1532-2882
DOI - 10.1002/asi.20872
Subject(s) - similarity (geometry) , relevance (law) , cosine similarity , pearson product moment correlation coefficient , citation , computer science , inference , information retrieval , co citation , citation analysis , correlation , similarity measure , statistical inference , data mining , statistics , mathematics , artificial intelligence , pattern recognition (psychology) , library science , geometry , political science , law , image (mathematics)
We provide in this article a number of new insights into the methodological discussion about author co‐citation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors' co‐citation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well‐known cosine. The other two similarity measures have not been used before in the bibliometric literature. We show by means of an example that the choice of an appropriate similarity measure has a high practical relevance. Finally, we discuss the use of similarity measures for statistical inference.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom