Open AccessAnalyzing cross‐reference transactions between authors by use of an asymmetric proximity measure and multidimensional unfolding
Author(s) -
Schneider Jesper W.,
Borlund Pia
Publication year - 2009
Publication title -
proceedings of the american society for information science and technology
Language(s) - English
Resource type - Journals
eISSN - 1550-8390
pISSN - 0044-7870
DOI - 10.1002/meet.2009.1450460244
Subject(s) - measure (data warehouse) , set (abstract data type) , computer science , odds , space (punctuation) , citation , multidimensional data , data science , data mining , theoretical computer science , machine learning , world wide web , logistic regression , programming language , operating system
The present paper explores simultaneous modelling of cross‐reference activity between authors by use of asymmetric proximities and multidimensional unfolding. We thereby model and map both citing and cited relations between authors in a common space. This enables a more comprehensive comparison of the author's dual roles of citing and being cited in a reference network. We model a set of 31 authors and compare the results to a recent author co‐citation study of Information Science. We find that multidimensional unfolding is a reliable and insightful technique for modelling authors' citing and cited dimensions simultaneously. The common space of citing and cited positions exemplify that some authors have substantial discrepancies between their citing behaviour and the way their works are used by peers in the set. Further, modelling mutual relationships as asymmetric brings more accuracy and nuances into the maps as relationships become overt. Finally, the study discusses how high publication activity influences mapping results considerably. To counter this effect, we demonstrate the appropriateness of correcting data for main effects by use of an asymmetric proximity measure of odds ratios.