Name
Abstract | ||
|---|---|---|
We present a meta-analysis of Big Data research activity since 2009. Our purpose here is to present \"tech mining\" (bibliometric and text analyses of research publication abstract record sets) to provide a research landscape of who is doing what, where, and when. Our larger purpose is to help Forecast Innovation Pathways for big data & analytics over the coming decade. We download 7006 research publication abstracts from Web of Science resulting from a search algorithm devised to recall a high percentage of core Big Data research and a moderate percentage of peripherally related research (fair recall). We find interesting engagement of different disciplines in Big Data over time. On a national level, the USA and China dominate these fundamental research publications to a striking degree. Mapping topics presents interesting evidence on what topics are emerging in this dynamic field. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/BigDataCongress.2015.44 | BigData Congress |
Keywords | Field | DocType |
Big Data, Tech Mining, Multidisciplinarity, Bibliometrics | Data science,Data mining,Metadata,World Wide Web,Search algorithm,Multidisciplinary approach,Computer science,Download,Bibliometrics,Analytics,Recall,Big data | Conference |
ISSN | Citations | PageRank |
2379-7703 | 3 | 0.50 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alan L. Porter | 1 | 398 | 32.61 |
| Ying Huang | 2 | 31 | 6.96 |
| Jannik Schuehle | 3 | 19 | 1.23 |
| Jan L. Youtie | 4 | 76 | 7.99 |