Evaluation of international academic journals in marketing with text mining method

Today, most of the data is in unstructured format. It is difficult to process data, conduct large volumes of data and access these data. Concequently, studies have been carried out on systems that are trying to improve the data organization in order to transform the data into processable form. Text mining is a set of processes that allow to uncover previously unknown relationships within unstructured texts. In our study, it is aimed to evaluate the academic journals which are published in marketing field with text mining approach. Gaps in the study area and the orientation of the area were determined and a study was conducted as a guide fort he researchers who wanted to do research in this field. For this purpose, data were obtained from the SCOPUS database with text mining from 16069 abstract articles published in 25 journals between 2005 and 2018. R programming language was used in the pre-processing stage of the data. According to the results of the analysis, a general picture of the literature in marketing field was published. The study areas within the scope of the determined subject indices have been determined. A journal recommendation model has been created in which researchers can send their publications. Journal-based researches and the transformations of journals over the years have been examined.