
Along with more and faster accumulation of electronic business data, Data Mining and the newer Big Data issues are attracting more attention. This paper reports the literature analysis based on the publication journals and articles in the research databases. The ranking comparisons of top 10 article counts in 2014 on Data Mining and Big Data show that there are 9 in common in the top 10 author countries but only 2 in common in the top 10 author organisations. There are 6 in common in the top 10 research areas but only 2 in common in the top 10 journal names. However, near 1/3 authors contributing to the Big Data literature come from the pool of authors who have publications in the Data Mining subject. Hopefully, their Big Data research in the value dimension may link better to the Data Mining knowledge and methodologies.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
