Keyword Analysis of Intellectual Capital and Knowledge Management in SCOPUS

The aim of this paper is to perform a keyword analysis in two areas of research: Intellectual Capital and Knowledge Management. The keywords are of three types : keywords proposed by the authors in their articles, the keywords that users use in their queries and the densest words existing in a textual corpus. Zipf's law usually applied for natural language is applied in this work for scientifc corpus constituted of confused full articles in each area. We wrote 8 R programs going through titles of articles, authors' keywords, abstracts and full articles to calculate frequencies and interpret them. The keywords of intellectual capital measurement and diclosure have the highest frequencies. The measures are stated by companies in annual reports and could not be integrated in their balance sheets because the classical accounting does not take into acount intellectual capital as an asset. Knowledge management is more oriented towards the capitalization of knowledge to improve business performance and for industries. This work is the first in keyword analysis for the two areas. It could be usefull to prepare glossaries, ontologies and all semantic reasearhes of research areas.