Prior Steps into Knowledge Mapping: Text Mining Application and Comparison

Abstract

Bibliometrics is increasingly being used by the knowledge community and librarians to easily analyze patterns in knowledge. In the field, the use of data from databases that provide bibliometric information is not always completely clean, so pre-processing is required. Several previous studies have shown that bibliometric analysis begins with a simple pre-processing step. The goal of this research is to use text mining to perform pre-processing to find the basic terms of the keywords that appear – to essentially construct a controlled vocabulary for a bibliographic dataset. The method used in this study is cleaning keywords with the stemming method using RapidMiner software. Bibliometrix was used to compare the results. A total of 85 keywords were combined into basic words. Using the built process, this study discovers differences in the network built between raw data and data that has been pre-processed, resulting in differences in the analysis that will be produced. The built process can also be reused in a variety of real-world situations.