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Abstract

Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1759-17676

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Abstract

Can maps of science tell us anything about paradigms? The author reviews his earlier work an this question, including Kuhn's reaction to it. Kuhn's view of the role of bibliometrics differs substantially from the kinds of reinterpretations of paradigms that information scientists are currently advocating. But these reinterpretations are necessary if his theory will ever be empirically tested, and further progress is to be made in understanding the growth of scientific knowledge. A new Web tool is discussed that highlights rapidly changing specialties that may lead to new ways of monitoring revolutionary change in real time. It is suggested that revolutionary and normal science be seen as extremes an a continuum of rates of change rather than, as Kuhn originally asserted, as an all or none proposition.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.5, S.394-399

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Source

Journal of the American Society for Information Science and Technology. 59(2008) no.11, S.1856-1860