Subject Domain Models of Jurisprudence According to Google Scholar Scientometrics Data
Abstract. The paper considers the approach to the network structuring of concepts of the selected subject domain based on the data contained in the Google
Scholar online scientometrics documentary resource. We present the methods
used in the creation of the subject domain models as networks of the terms of a
specific topic, which correspond to the basic concepts within the specified theme.
In particular, in this work, we use the networks of natural hierarchies of terms .
the algorithm for creating the directed network of words and phrases for thematic
text corpora as a terminological model. Based on the freely accessible search engine which indexes the full text of scientific publications . Google Scholar for
the thematic queries it was pre-prepared the text corpora. Within the scope of this
work, the so-called networks of natural hierarchies of terms are considered for
the corpus of scientific articles related to the subject domains of "Criminal Law"
and "Copyright Law". The considered in this work processes were automated by
using the NLTK library of the Python programing language. The obtained networks of natural hierarchies of terms for "Criminal Law" and "Copyright Law"
were visualized and analyzed. The considered techniques of creation of such networks and the implementation of the algorithm for creating the directed networks
of terms will contribute to the formation and improvement of the conceptual and
terminological apparatus in the legal sphere and the harmonization of national
and international legislation.