|Authors||K. Pogorelov, D. T. Schroeder, P. Filkukova and J. Langguth|
|Title||A System for High Performance Mining on GDELT Data|
|Project(s)||UMOD: Understanding and Monitoring Digital Wildfires|
|Publication Type||Proceedings, refereed|
|Year of Publication||2020|
|Conference Name||2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)|
|Keywords||Data mining, GDELT, High Performance Computing, Misinformation, Publishing|
We design a system for efficient in-memory analysis of data from the GDELT database of news events. The specialization of the system allows us to avoid the inefficiencies of existing alternatives, and make full use of modern parallel high-performance computing hardware. We then present a series of experiments showcasing the system’s ability to analyze correlations in the entire GDELT 2.0 database containing more than a billion news items. The results reveal large scale trends in the world of today’s online news.