Usage Impact Factor: The effects of sample characteristics on usage-based impact metrics

There exist ample demonstrations that indicators of scholarly impact analogous to the citation-based ISI Impact Factor can be derived from usage data; however, so far, usage can practically be recorded only at the level of distinct information services. This leads to community-specific assessments of scholarly impact that are difficult to generalize to the global scholarly community. In contrast, the ISI Impact Factor is based on citation data and thereby represents the global community of scholarly authors. The objective of this study is to examine the effects of community characteristics on assessments of scholarly impact from usage. We define a journal Usage Impact Factor that mimics the definition of the Thomson Scientific ISI Impact Factor. Usage Impact Factor rankings are calculated on the basis of a large-scale usage dataset recorded by the linking servers of the California State University system from 2003 to 2005. The resulting journal rankings are then compared to the Thomson Scientific ISI Impact Factor that is used as a reference indicator of general impact. Our results indicate that the particular scientific and demographic characteristics of a discipline have a strong effect on resulting usage-based assessments of scholarly impact. In particular, we observed that as the number of graduate students and faculty increases in a particular discipline, Usage Impact Factor rankings will converge more strongly with the ISI Impact Factor.