A Novel Method for Visualizing Keywords in Bibliometrics Science

Abstract

In the last two decades bibliometrics science has been evolving to help scientists and researchers to maintain the drastically increasing of the availability of scienti c literature. Bibliometrics help to have a broad understanding of an intended scienti c eld by providing multiple levels of methods and tools to analysis the literature of that scienti c eld. Unfortunately, the bibliometrics science is a quantitative method that use basic math to assess author outputs by h-index, articles impact by counting citations, or journal by its impact factor. Thus, the objective of this dissertation is to pave a solid path to integrate qualitative method into the emerging eld of bibliometrics science. For that, I am going to : (1) apply the bibliometrics methodology on the literature of the statistics eld by giving a visual representation of the bibliographic data of the eld, that will identify emerging trends and understanding relationships between di erent developments in the eld. Also, (2) study the similarity measures on the co-word analysis then introducing an integrated method between the quantitative and qualitative approaches to calculate the similarity between keywords in co-word analysis. Finally, (3) presenting the important of a better visualizing presentation of keywords on a 2D map by introducing a qualitative method to calculate the weight (strength) of keywords in clustering analysis, within bibliometrics data.