The value of using big data technologies in computational social science

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)
1 Downloads (Pure)

Abstract

The discovery of phenomena in social networks has prompted renewed interests in the field. Data in social networks however can be massive, requiring scalable Big Data architecture. Conversely, research in Big Data needs the volume and velocity of social media data for testing its scalability. Not only so, appropriate data processing and mining of acquired datasets involve complex issues in the variety, veracity, and variability of the data, after which visualisation must occur before we can see fruition in our efforts. This article presents topical, multimodal, and longitudinal social media datasets from the integration of various scalable open source technologies. The article details the process that led to the discovery of social information landscapes within the Twitter social network, highlighting the experience of dealing with social media datasets, using a funneling approach so that data becomes manageable. The article demonstrated the feasibility and value of using scalable open source technologies for acquiring massive, connected datasets for research in the social sciences.

Original languageEnglish
Title of host publicationProceedings of the 3rd ASE International Conference on Big Data Science and Computing, BIGDATASCIENCE 2014
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450328913
DOIs
Publication statusPublished - 4 Aug 2014
Event3rd ASE International Conference on Big Data Science and Computing, BIGDATASCIENCE 2014 - Beijing, China
Duration: 4 Aug 20147 Aug 2014

Publication series

NameACM International Conference Proceeding Series
Volume04-07-August-2014

Conference

Conference3rd ASE International Conference on Big Data Science and Computing, BIGDATASCIENCE 2014
Country/TerritoryChina
CityBeijing
Period4/08/147/08/14

Keywords

  • Computational social science
  • Data mining
  • Open source
  • Social network analysis
  • Twitter

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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