A resource efficient big data analysis method for the social sciences: The case of global IP activity

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This paper presents a novel and efficient way of analysing big datasets used in social science research. We provide and demonstrate a way to deal with such datasets without the need for high performance distributed computational facilities. Using an Internet census dataset and with the help of freely available tools and programming libraries, we visualize global IP activity in a spatial and time dimension. We observe a considerable reduction in storage size of our dataset coupled with a faster processing time.
Original languageEnglish
Title of host publication2014 International Conference on Computational Science (ICCS 2014)
EditorsDavid Abramson, Michael Lees, Valeria V. Krzhizhanovskaya, Jack Dongarra, Peter M.A. Sloot
Place of PublicationAmsterdam Netherlands
Number of pages10
Publication statusPublished - 2014
EventInternational Conference on Computational Science 2014 - Cairns, Australia
Duration: 10 Jun 201412 Jun 2014
Conference number: 14th

Publication series

NameProcedia Computer Science
ISSN (Electronic)1877-0509


ConferenceInternational Conference on Computational Science 2014
Abbreviated titleICCS 2014
OtherThe International Conference on Computational Science is an annual conference that brings together researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering computational methods in sciences such as physics, chemistry, life sciences, and engineering, as well as in arts and humanitarian fields, to discuss problems and solutions in the area, to identify new issues, and to shape future directions for research.

ICCS 2014 in Cairns, Queensland, will be the fourteenth in this series of highly successful conferences.
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  • Big data
  • Social sciences
  • Internet census
  • GIS
  • Memory reduction

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