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Author Bibliographic Coupling – Another approach to citation-based author knowledge network analysis

Dangzhi Zhao and Andreas Strotmann

ASIS&T 2008 Annual Meeting (AM08 2008)
Columbus, Ohio, October 24-29, 2008


Summary

While bibliographic coupling (BC) as a measure of relatedness between documents was proposed a full decade before co-citation, interest in applying BC to mapping the intellectual structure of research areas has only recently resurged, perhaps because it allows researchers to circumvent problems of the so far dominant co-citation analysis.

Especially for mapping the intellectual structure of a research field as represented by its authors, author co-citation analysis (ACA) has frequently been applied over the last two decades, but no author BC analysis has so far been attempted. Theoretically, the main limitations of ACA can be circumvented by author BC analysis: (1) While ACA maps the past (cited authors), author BC analysis maps the present (citing authors), thus supporting study of more current author knowledge networks. (2) Because the data sources that citation analysis studies rely on index all authors of each citing (source) paper but only the first author of each cited reference, ACA has been forced to only consider authors’ contributions as first authors whereas author BC analysis can easily also include authors’ contributions as non-first authors, allowing a less biased view of intellectual structures of research fields, especially highly collaborative fields.

In this paper, we define author BC and conduct an author BC analysis of the Information Science field using the same dataset as that used in our previous ACA study, which covers Information Science during 1996-2005. We find that these two citation-based author knowledge network analysis methods do indeed complement each other, with one providing a more realistic picture of the state of research within the IS field and the other revealing the structure of both internal and external influences on the IS research. In combination, the two methods provide a more comprehensive view of the intellectual structure of the IS field than either of them alone.


  
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