Impacts of Big Data on Data Mining Research: An Empirical Study of Chinese Journals

Abstract

With the advent of big data, data mining theories and methods face new challenges. This paper tries to find the impacts of big data on data mining research through 23377 data mining-related papers published in Chinese academic journals during 1996--2016. By utilization of various methods of bibliometrics, this study conducts three different levels of analysis to gradually dig deeper into the contents of literature. For the macro-level, paper amount analysis results show that big data-related research began in 2012 and has brought new growth to data mining area. For the meso-level, journal distribution analysis results indicate that many other disciplines, such as arts and agriculture science, began to apply data mining techniques with the wide spread of big data. For the micro-level, co-word-based research topic clustering results imply that new topics emerged due to the easy access of big data, such as 'clouding computing' and 'teaching and learning analysis'.