Big Data Research Landscape: A Meta-Analysis and Literature Review from 2009 to 2018

Big data is a relatively new and lively field of research and practice. Researchers investigating a new field of research are interested in themes, trends, and gaps that demonstrate the field in order to make informed and accurate choices. Understanding up to date trends and potential gaps in a research field is only possible through a detailed analysis of the domain-specific literature. Since scientific literature has an exponential growth, it is not easy to manually identify such trends. In this context, probabilistic topic modeling is an effective approach which has recently attracted considerable attention in semantic analysis of large-scale textual collections. In this study, a semantic content analysis based on topic modeling was conducted on big data literature from 2009 to 2018 in order to discover big data research trends and themes.

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