Demonstration the Importance of Pre‐processing the Text Fields of Bibliometric Records to Identify Promising Research Tasks. Case Study of Scopus Data on Petroleum Reservoir Engineering

Background. Nowadays, bibliometric analyses of data from abstract databases are often used to identify relevant research problems in order to rationalize the use of financial and other resources. The aim of this paper was to demonstrate the importance of pre-processing the text fields of bibliometric records to construct a term co-occurrence network and the feasibility of subsequently using Scimago Graphica to examine different slices of clustering results in detail in order to identify relevant research topics. Materials and Methods. A total of 8051 records exported from Scopus matching a filter (LIMIT-TO (EXACTKEYWORD, ‘Petroleum Reservoir Engineering’)) over the last ten years were used. VOSviewer and Scimago Graphica were applied for bibliometric analysis. The results of the study showed the relevance of using the filter ‘LIMIT-TO EXACTKEYWORD’ in the query to Scopus; the expediency of disclosing abbreviations in the text fields of records and preliminary clarification of texts; the effectiveness of using filters in the Scimago Graphica program to build a network of co-currency of terms in order to identify promising research topics; the proposal of promising research objectives arising from the analysis, which can be described by the following terms: 1. nanopores, shale oil, pore size, molecular; 2. nanoparticles; 2. It is observed that in some cases terms occurring in the same cluster are not the best choice for querying in order to expand the collection of publications on a given topic. Therefore, it is proposed to conduct a separate study using Apriori class algorithms for this purpose.