The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments, and report on experiments that demonstrate their effectiveness in a variety of contexts on the World Wide Web. The central issue we address within our framework is the distillation of broad search topics, through the discovery of “authoritative ” information sources on such topics. We propose and test an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of “hub pages ” that join them together in the link structure. Our formulation has connections to the eigenvectors of certain matrices associated with the link graph; these connections in turn motivate additional heuristics for link-based analysis.

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An important characteristic of journals is how influential they are in the generation and dissemination of scholarly knowledge in a discipline. We report a citation analysis of 49 marketing and marketing-related journals to assess their relative influence based on the index of structural influence proposed by Salancik (1986). We investigate the level and span of influence of the 49 journals, both in the marketing discipline as a whole and in five specific sub-areas of marketing. As expected, the Journal of Marketing emerges as the most influential journal in the discipline and as the journal with the broadest span of influence across all sub-areas of marketing. However, different journals are most influential in each of the sub-areas, and the Journal of Marketing is particularly influential among the applied marketing journals. We also find that the index of structural influence is significantly correlated with all other measures of influence but least so with the impact factors report...