Search

Abstract: Recitation patterns for individual publications are examined and mathematically modeled by focusing on the origin of citations (citers) using data from Thomson Reuters Web of Science. The authors outline oeuvre citation exhaustivity, or the practice of citing across the body of work of an author, and model the resulting frequency distributions to identify research disciples and admirers. A Geeta distribution provided the best fits for both recitation frequency and oeuvre citation exhaustivity distributions. The findings provide a novel way to identify the influence of an author based on citer analysis. [Copyright &y& Elsevier]

Two large data sets of queries submitted to the Excite search service were used to derive different distributions of query and search behaviours (query-term usage across queries, terms used per query, page requests per query, queries per user/ session, query frequency across users). The authors fitted each data set to theoretical models used in Informetric research, in additional to the standard Zipf model to which most frequency distributions of Internet usage phenomena are informally fitted. The generalized inverse Gaussian-Poisson distribution provided the best fits for the models tested. With more accurate models to represent observed Web usage behaviours, researchers will be better able to simulate user behaviours. [ABSTRACT FROM AUTHOR]

The influence of sample size on informetric characteristics is examined to determine whether theoretical mathematical models can adequately fit large data sets. Two large data sets of queries submitted to the Excite search service were sampled for search characteristics (term frequencies, terms used per query, pages viewed per query, queries submitted per session) producing data sets of various sizes that were fitted to theoretical models to determine how the sample may influence a model's goodness-of-fit. Although theoretical models could adequately fit smaller data sets of up to 5000 observations in some cases, larger data sets could not be satisfactorily fitted using several goodness-of-fit techniques. Investigators must take into account that sample size does influence goodness-of-fit outcomes. The nature of the data and not the limitations of given goodness-of-fit tests results in significant outcomes. Such goodness-of-fit tests should be used for comparative purposes, rather than significance testing. [ABSTRACT FROM AUTHOR]