A scientometric analysis of big data literature

Big data is a broad term for so large and complex data collections that traditional data processing applications are inadequate. A new field, Predictive Analytics, is trying to extract value from this big (unstructured) data. The purpose of this paper is to analyze the content and citation of the articles published on data is numerous. This study analyzes the content and citation of 49 articles published in 2012-2016. In this study, necessary information was collected using content and references to individual categories and articles and then SPSS 18 was used. In analyzing the data, descriptive statistics, including data classified according to frequency distribution and graphs were used. It also reviews significant trends in Big Data; Rapidminer5.3 was used. The results of this study provide a better understanding of patterns, trends and other important factors as a basis for directing research activities, sharing knowledge and collaborating in the area of big data research.