Real-time GPU-accelerated social media sentiment processing and visualization

Eugene Ch'ng, Ziyang Chen, Simon See

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

1 Citation (Scopus)

Abstract

Data visualization is an important aspect of data analytics in an age where decisions are all based on information. Approaches in data visualization, particularly those that have the capability of processing large-scale textual datasets and visualize them as structured information in real-time can be useful for monitoring trends in social media. In this article, we present our GPU accelerated project, which uses CUDA to distribute and parallelize the processing and analysis of textual data in order to visualize information in real-time, or close to real-time as a foundational system for the future of real-time applications which monitors trends in social media, applicable to political elections, social media analytics, and other needs in computational social sciences which are time-critical.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017
EditorsAlfredo Garro, Andrea D'Ambrogio, Robson De Grande, Andrea Tundis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781538640289
DOIs
Publication statusPublished - 5 Dec 2017
Event21st IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017 - Rome, Italy
Duration: 18 Oct 201720 Oct 2017

Publication series

NameProceedings - 2017 IEEE/ACM 21st International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017
Volume2017-January

Conference

Conference21st IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2017
Country/TerritoryItaly
CityRome
Period18/10/1720/10/17

Keywords

  • Big data
  • GPU acceleration
  • Real-time visualization
  • Sentiment analysis
  • Social media
  • Twitter

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications

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